# kb

id: list-of-experiments-20260505-0
file: data/en.wikipedia.org/wiki/List_of_experiments-0.md
category: reference
title: List of experiments
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_experiments
date_saved: 2026-05-05T09:56:27.280362+00:00
instance: kb-cron
parent: list-of-experiments-20260505-0
summary:
The following is a list of historically important scientific experiments and observations demonstrating something of great scientific interest, typically in an elegant or clever manner. == Astronomy == Ole Rømer makes the first quantitative estimate of the speed of light in 1676 by timing the motions of Jupiter's satellite Io with a telescope Arno Penzias and Robert Wilson detect the cosmic microwave background radiation, giving support to the theory of the Big Bang (1964) Kerim Kerimov launches Kosmos 186 and Kosmos 188 as experiments on automatic docking eventually leading to the development of space stations (1967) The Supernova Cosmology Project and the High-Z Supernova Search Team discover, by observing Type Ia supernovae, that the expansion of the Universe is accelerating (1998) Galileo Galilei uses a telescope to observe that the moons of Jupiter appear to circle Jupiter. This evidence supports the heliocentric model, and weakens the geocentric model of the cosmos (1609) == Biology == Robert Hooke, using a microscope, observes cells (1665). Anton van Leeuwenhoek discovers microorganisms (1674–1676). James Lind, publishes 'A Treatise of the Scurvy' which describes a controlled shipboard experiment using two identical populations but with only one variable, the consumption of citrus fruit (1753). Edward Jenner


id: list-of-experiments-20260505-1
file: data/en.wikipedia.org/wiki/List_of_experiments-1.md
category: reference
title: List of experiments
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_experiments
date_saved: 2026-05-05T09:56:27.280362+00:00
instance: kb-cron
parent: list-of-experiments-20260505-0
summary:
== Chemistry == Robert Boyle uses an air pump to determine the inverse relationship between the pressure and volume of a gas. This relationship came to be known as Boyle's law (1660–1662). Joseph Priestley suspends a bowl of water above a beer vat at a brewery and synthesizes carbonated water (1767). Antoine Lavoisier determines that oxygen combines with materials upon combustion, thus disproving phlogiston theory (1783). Antoine Lavoisier determines that chemical reactions in a closed container do not alter total mass. From these observations he establishes the law of conservation of mass (1789). Benjamin Thompson, Count Rumford demonstrates that the heat developed by the friction of boring cannon is nearly inexhaustible. This result was presented in opposition to caloric theory (1798). Humphry Davy uses electrolysis to isolate elemental potassium, sodium, calcium, strontium, barium, magnesium, and chlorine (1807–1810). Joseph Louis Gay-Lussac studies reactions among gases and determines that their volumes combine chemically in simple integer ratios (1809). Robert Brown studies very small particles in water under the microscope and observes Brownian motion which was later named in his honor (1827). Friedrich Wöhler synthesizes the organic compound urea using inorganic reactants, disproving the application of vitalism to chemical processes (1828). Thomas Graham


id: list-of-experiments-20260505-2
file: data/en.wikipedia.org/wiki/List_of_experiments-2.md
category: reference
title: List of experiments
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_experiments
date_saved: 2026-05-05T09:56:27.280362+00:00
instance: kb-cron
parent: list-of-experiments-20260505-0
summary:
Inclined plane experiment (1602–07): Galileo Galilei uses rolling balls to disprove the Aristotelian theory of motion. Atmospheric pressure vs. altitude experiment (1648): Blaise Pascal carries a barometer up a church tower and a mountain to determine that atmospheric pressure is due to a column of air. Magdeburg hemispheres (1654): Otto von Guericke demonstrates atmospheric pressure using a pair of hollow copper hemisphere. Spring of air experiment (1660): Robert Boyle shows that the volume of a given amount of gas is inversely related to the pressure upon it. Kite experiment (1700s): Benjamin Franklin beginning in 1747 describes experiments in letters to Peter Collinson demonstrating electrical principles which were published in a book called Experiments and Observations on Electricity. Voltaic pile (1796): Alessandro Volta constructs a new source of electricity, the electrical battery. Cavendish experiment (1798): Henry Cavendish's torsion bar experiment measures the force of gravity in a laboratory. Double-slit experiment (c.1805): Thomas Young shows that light is a wave in his double-slit experiment. Arago spot (1819): Observation of circular diffraction by François Arago, validated a new wave theory of light by Augustin-Jean Fresnel disproving skeptics like Siméon Denis Poisson. Ørsted experiment (1820): Hans Christian Ørsted demonstrates the connection of electricity and


id: acali-20260505-0
file: data/en.wikipedia.org/wiki/Acali-0.md
category: reference
title: Acali
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Acali
date_saved: 2026-05-05T09:56:28.400557+00:00
instance: kb-cron
parent: acali-20260505-0
summary:
The Acali expedition (or Acali experiment or the Sex Raft) was a 1973 social experiment that aimed to investigate interpersonal relationships in conditions of limited space and social isolation. The experiment was conceived by Mexican anthropologist Santiago Genovés, who had previously been a crew member of Thor Heyerdahl's Ra expedition. The participants showed a restraint towards aggression, which frustrated Genovés and led him to start to try to create conflict, and at one point he took command of the float. Despite these attempts, the group remained peaceful. The raft had a complement of eleven people: five men and six women. It left Las Palmas, Spain, on 12 May 1973 and took 101 days to drift across the Atlantic Ocean and reach Cozumel, Mexico, with a single stopover in Barbados. Frequently dubbed the "Sex Raft" by the media, it was the subject of a 2018 documentary film The Raft, by Marcus Lindeen. == The Raft == The name of the raft, Acali, comes from the Nahuatl language and means "the house on the water". The raft was built specifically for the experiment. It had a steel hull and dimensions of 12 by 7 metres. The cabin measured 4 × 4 metres.


id: aircraft-nuclear-propulsion-20260505-0
file: data/en.wikipedia.org/wiki/Aircraft_Nuclear_Propulsion-0.md
category: reference
title: Aircraft Nuclear Propulsion
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Aircraft_Nuclear_Propulsion
date_saved: 2026-05-05T09:56:29.596684+00:00
instance: kb-cron
parent: aircraft-nuclear-propulsion-20260505-0
summary:
The Aircraft Nuclear Propulsion (ANP) program and the preceding Nuclear Energy for the Propulsion of Aircraft (NEPA) project worked to develop a nuclear propulsion system for aircraft. The United States Army Air Forces initiated Project NEPA on May 28, 1946. NEPA operated until May 1951, when the project was transferred to the joint Atomic Energy Commission (AEC)/USAF ANP. The USAF pursued two different systems for nuclear-powered jet engines, the Direct Air Cycle concept, which was developed by General Electric, and Indirect Air Cycle, which was assigned to Pratt & Whitney. The program was intended to develop and test the Convair X-6, but was canceled in 1961 before that aircraft was built. The total cost of the program from 1946 to 1961 was about $1 billion. == Types == === Direct air cycle === Direct cycle nuclear engines resemble a conventional jet engine without combustion chambers. The hot compressed air produced by the compressor section is instead directed into the nuclear reactor core. The air is heated further, thereby cooling the reactor. The air is then expanded through a turbine, powering the compressor, before it is exhausted at high velocity to provide thrust. The end result is that instead of using


id: aircraft-nuclear-propulsion-20260505-1
file: data/en.wikipedia.org/wiki/Aircraft_Nuclear_Propulsion-1.md
category: reference
title: Aircraft Nuclear Propulsion
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Aircraft_Nuclear_Propulsion
date_saved: 2026-05-05T09:56:29.596684+00:00
instance: kb-cron
parent: aircraft-nuclear-propulsion-20260505-0
summary:
=== Pratt & Whitney Aircraft Reactor-1 === On February 5, 1957, another reactor was made critical at the Critical Experiments Facility of the Oak Ridge National Laboratory (ORNL) as part of the circulating-fuel reactor program of the Pratt & Whitney Aircraft Company (PWAC). This was called the PWAR-1, the Pratt & Whitney Aircraft Reactor-1. The purpose of the experiment was to experimentally verify the theoretically predicted nuclear properties of a PWAC reactor. The experiment was only run briefly; by the end of February 1957 all data had been taken and disassembly had begun. The experiment was run at essentially zero nuclear power. The operating temperature was held constant at approximately 675 °C (1,247 °F), which corresponds closely to the design operating temperature of the PWAR-l moderator; this temperature was maintained by external heaters. Like the 2.5 MWt ARE, the PWAR-1 used NaF-ZrF4-UF4 as the primary fuel and coolant. == Cancellation == Technological competition with the Soviet Union (as represented by the launch of Sputnik 1), and continued strong support from the Air Force allowed the program to continue, despite divided leadership between the DOD and the AEC. Numerous test facilities were funded and constructed through the 1950s and 1960–61 in


id: bataan-rice-enrichment-project-20260505-0
file: data/en.wikipedia.org/wiki/Bataan_Rice_Enrichment_Project-0.md
category: reference
title: Bataan Rice Enrichment Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bataan_Rice_Enrichment_Project
date_saved: 2026-05-05T09:56:30.770293+00:00
instance: kb-cron
parent: bataan-rice-enrichment-project-20260505-0
summary:
Bataan Rice Enrichment Project or the Bataan Experiment, was a collaborative research venture between American chemist Robert R. Williams and Juan Salcedo Jr. It was a series of feeding experiments conducted in municipalities in Bataan between 1947 and 1949. By the end of the experiments, it is shown that thiamine-enriched rice can reduce the cases of beriberi in the Philippines, which was the leading cause of deaths during those times. == Overview == The enrichment project came first as a plan in 1943. During this time, Salcedo, who had his studies at Columbia University, met American chemist Robert R. Williams, a well renowned scientist for his synthesis on vitamin B1 in 1935. The Philippine Bureau of Health reported a relatively stable beriberi rate from the mid-1920s to 1940. However, after World War II, beriberi cases surged, becoming the second leading cause of death in 1946 and 1947. Infants accounted for a significant portion of these deaths. At this time, Williams was disappointed by the agencies at the United Nations to further eradicate the rise of beriberi cases around the globe. Due to his previous failures in rice enrichment programs, Williams became desperate. Together with Salcedo, they began feeding experiments in


id: behavioral-experiment-20260505-0
file: data/en.wikipedia.org/wiki/Behavioral_experiment-0.md
category: reference
title: Behavioral experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Behavioral_experiment
date_saved: 2026-05-05T09:56:31.895442+00:00
instance: kb-cron
parent: behavioral-experiment-20260505-0
summary:
Technically, all scientific experiments measure a change in hypothesized causal behavior, and may drop the behavioral prefix. Behavioral experiment may refer to: Behavioral experiment (analysis) Behavioral experiment (animals), for controlling variables (vs. field studies) Behavioral experiment (cognitive science), for determining what constitutes intelligent behavior Behavioral experiment (cognitive therapy), method for cognitive restructuring Behavioral experiment (cognitive behavioral therapy), for testing the validity of negative and alternative thoughts in real-life situations Behavioral experiment (computational modeling), of computational model for comparison with human data Behavioral experiment (experimental psychology), for measuring reaction time, choices among alternatives, and/or response rate or strength Behavioral experiment (human reasoning), for studying human reasoning Behavioral experiment (conditional reasoning), on conditionals in the psychology of reasoning Behavioral experiment (psychotherapy), for identifying potentially negative or harmful beliefs == See also == Behavioral experiments for monotropism Behaviorism, which is based on such experiments Experiment Category:Science experiments All pages with titles containing experiment Behavior All pages with titles containing behavior All pages with titles containing behaviour


id: cloud-seeding-in-the-united-arab-emirates-20260505-0
file: data/en.wikipedia.org/wiki/Cloud_seeding_in_the_United_Arab_Emirates-0.md
category: reference
title: Cloud seeding in the United Arab Emirates
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cloud_seeding_in_the_United_Arab_Emirates
date_saved: 2026-05-05T09:56:33.076239+00:00
instance: kb-cron
parent: cloud-seeding-in-the-united-arab-emirates-20260505-0
summary:
Cloud seeding in the United Arab Emirates is a weather modification technique used by the government to address water challenges in the country. Cloud seeding is also referred to as man made precipitation and artificial rain making. The United Arab Emirates is one of the first countries in the Persian Gulf region to use cloud seeding technology. UAE scientists use cloud seeding technology to supplement the country's water insecurity, which stems from the extremely hot climate. They use weather radars to continuously monitor the atmosphere of the country. Forecasters and scientists have estimated that cloud seeding operations can enhance rainfall by as much as 30-35% percent in a clear atmosphere, and up to 10-15% in a more humid atmosphere. This practice has caused concerns regarding the impact on the environment because it is difficult to predict its long-term global implications. == Climate needs == The UAE has an arid climate with less than 100mm per year of rainfall, a high evaporation rate of surface water and a low groundwater recharge rate. Rainfall in the UAE has been fluctuating over the last few decades in winter season between December and March. The climate of the UAE is very dry aside from


id: cloud-seeding-in-the-united-arab-emirates-20260505-1
file: data/en.wikipedia.org/wiki/Cloud_seeding_in_the_United_Arab_Emirates-1.md
category: reference
title: Cloud seeding in the United Arab Emirates
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cloud_seeding_in_the_United_Arab_Emirates
date_saved: 2026-05-05T09:56:33.076239+00:00
instance: kb-cron
parent: cloud-seeding-in-the-united-arab-emirates-20260505-0
summary:
=== Flooding === It is predicted that climate change will lead to higher temperatures, increased humidity and a greater risk of flooding in parts of the Gulf region. These issues could be worsened in nations like the UAE which do not have adequate drainage infrastructure to manage heavy rainfall. Cloud seeding activities conducted in 2019 by the UAE National Center of Meteorology & Seismology (NCM) as part of the UAE Research Program for Rain Enhancement Science were carried out prior to floods in Dubai in 2019. Although the NCM has linked heavier rainfall to cloud seeding operations, they assert it was not the cause of the flooding. Commercial and residential areas were severely impacted and pumps were needed to remove excess water due to inadequate drainage systems because drainage systems could not handle the volume of water. The UAE planned to invest 500 million dirhams ($136.1 million) on flood protection and transport infrastructure after severe storms in 2020. Sharjah, one of the most populous cities in the UAE, has experienced repetitive urban flooding during the rainy season over the last three decades. Possible additional increased rainfall intensity due to cloud seeding would require additional investment in the city's drainage systems


id: control-variable-20260505-0
file: data/en.wikipedia.org/wiki/Control_variable-0.md
category: reference
title: Control variable
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Control_variable
date_saved: 2026-05-05T09:56:34.251757+00:00
instance: kb-cron
parent: control-variable-20260505-0
summary:
A control variable (or scientific constant) in scientific experimentation is an experimental element which is constant (controlled) and unchanged throughout the course of the investigation. Control variables could strongly influence experimental results were they not held constant during the experiment in order to test the relative relationship of the dependent variable (DV) and independent variable (IV). The control variables themselves are not of primary interest to the experimenter. "Good controls", also known as “confounders” or “deconfounders”, are variables which are theorized to be unaffected by the treatment and which are intended to eliminate omitted-variable bias. "Bad controls", on the other hand, are variables that could be affected by the treatment, might contribute to collider bias, and lead to erroneous results. == Usage == A variable in an experiment which is held constant in order to assess the relationship between multiple variables, is a control variable. A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested. In any system existing in a natural state, many variables may be interdependent, with each affecting the other. Scientific experiments test the relationship of an IV


id: eddington-experiment-20260505-0
file: data/en.wikipedia.org/wiki/Eddington_experiment-0.md
category: reference
title: Eddington experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eddington_experiment
date_saved: 2026-05-05T09:56:35.485516+00:00
instance: kb-cron
parent: eddington-experiment-20260505-0
summary:
The Eddington experiment was an observational test of general relativity, organised by the British astronomers Frank Watson Dyson and Arthur Stanley Eddington in 1919. Observations of the total solar eclipse of 29 May 1919 were carried out by two expeditions, one to the West African island of Príncipe, and the other to the Brazilian town of Sobral. The aim of the expeditions was to measure the gravitational deflection of starlight passing near the Sun. The amount of deflection was predicted by Albert Einstein in a 1911 paper; however, his initial prediction proved inaccurate because it was based on an incomplete theory of general relativity. Einstein improved his prediction after finalizing his theory in 1915 and obtaining the solution to his equations by Karl Schwarzschild. Following the return of the expeditions, the results were presented by Eddington to a joint meeting of the Royal Society and Royal Astronomical Society in London and, after some deliberation, were accepted. Widespread newspaper coverage of the results led to worldwide fame for Einstein and his theories. == Background == One of the first considerations of gravitational deflection of light was published in 1801, when Johann Georg von Soldner pointed out that Newtonian gravity predicts that


id: eddington-experiment-20260505-1
file: data/en.wikipedia.org/wiki/Eddington_experiment-1.md
category: reference
title: Eddington experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eddington_experiment
date_saved: 2026-05-05T09:56:35.485516+00:00
instance: kb-cron
parent: eddington-experiment-20260505-0
summary:
== Theory == The theory behind the experiment concerns the predicted deflection of light by the Sun. The first observation of light deflection was performed by noting the change in position of stars as they passed near the Sun on the celestial sphere. The approximate angular deflection δφ for a massless particle coming in from infinity and going back out to infinity is given by the following formula: δ φ ≈ 2 r s b = 4 G M c 2 b . {\displaystyle \delta \varphi \approx {\frac {2r_{s}}{b}}={\frac {4GM}{c^{2}b}}.} Here, b can be interpreted as the distance of closest approach. Although this formula is approximate, it is accurate for most measurements of gravitational lensing, due to the smallness of the ratio rs/b. For light grazing the surface of the Sun, the approximate angular deflection is roughly 1.75 arcseconds. This is twice the value predicted by calculations using the Newtonian theory of gravity. It was this difference in the deflection between the two theories that Eddington's expedition and other later eclipse observers would attempt to observe. == Expeditions and observations == The aim of the expeditions was to take advantage of the shielding effect of the Moon during a total


id: eddington-experiment-20260505-2
file: data/en.wikipedia.org/wiki/Eddington_experiment-2.md
category: reference
title: Eddington experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eddington_experiment
date_saved: 2026-05-05T09:56:35.485516+00:00
instance: kb-cron
parent: eddington-experiment-20260505-0
summary:
=== Príncipe === The equipment used for the expedition to Príncipe, an island in the Gulf of Guinea off the coast of West Africa, was an astrographic lens borrowed from the Radcliffe Observatory in Oxford. Eddington sailed from England in March 1919. By mid-May he had his equipment set up on Príncipe near what was then Spanish Guinea. The eclipse was due to take place in the early afternoon of 29 May, at 2 pm, but that morning there was a storm with heavy rain. Eddington wrote: The rain stopped about noon and about 1.30 ... we began to get a glimpse of the sun. We had to carry out our photographs in faith. I did not see the eclipse, being too busy changing plates, except for one glance to make sure that it had begun and another half-way through to see how much cloud there was. We took sixteen photographs. They are all good of the sun, showing a very remarkable prominence; but the cloud has interfered with the star images. The last few photographs show a few images which I hope will give us what we need ... Eddington developed the photographs on Príncipe, and attempted to measure


id: eddington-experiment-20260505-3
file: data/en.wikipedia.org/wiki/Eddington_experiment-3.md
category: reference
title: Eddington experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eddington_experiment
date_saved: 2026-05-05T09:56:35.485516+00:00
instance: kb-cron
parent: eddington-experiment-20260505-0
summary:
The presentation of the results at the joint 6 November 1919 session of Royal Society and Royal Astronomical Society led to intensive press coverage first in Great Britain and a few days later in the US press, notably in The New York Times, and some days later still in the German press. While Einstein had been a moderately famous public figure in Germany for a few years by that time, the articles in question marked the beginning of his international celebrity status. A notable exception was Belgium, where the Eddington results were given the cold shoulder – partly because Einstein was seen as representing Germany, with the suffering of Belgium in World War I still very present in the country. The sudden popularity of Einstein's theories led to an "Einstein boom" of popular science books. While there is a later anecdote describing Einstein as unimpressed about the experimental results, and sure of his theory even in the absence of evidence (stating, when asked what he would have said if the results had been otherwise, "Then I would feel sorry for the dear Lord. The theory is correct anyway.") the evidence of Einstein's letters to other scientists indicates, on the contrary,


id: eddington-experiment-20260505-4
file: data/en.wikipedia.org/wiki/Eddington_experiment-4.md
category: reference
title: Eddington experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eddington_experiment
date_saved: 2026-05-05T09:56:35.485516+00:00
instance: kb-cron
parent: eddington-experiment-20260505-0
summary:
== Sources and further reading == Collins, Harry; Pinch, Trevor (1993). The Golem: What everyone should know about science. Cambridge University Press. ISBN 0521477360. Cowen, Ron (May 2019). Gravity's Century: From Einstein's Eclipse to Images of Black Holes (Illustrated ed.). Harvard University Press. ISBN 978-0-674-97496-8. Crelinsten, Jeffrey (May 2006). Einstein's Jury: The Race to Test Relativity. Princeton University Press. ISBN 978-0-691-12310-3. Gates, Sylvester J. Jr; Pelletier, Cathie (2019). Proving Einstein right: The daring expeditions that changed how we look at the universe (First ed.). New York: PublicAffairs. ISBN 978-1541762251. Kennefick, Daniel (2019). No Shadow of a Doubt: The 1919 Eclipse That Confirmed Einstein's Theory of Relativity. Princeton: Princeton University Press. ISBN 9780691183862. Popper, Karl (2002) [1935]. The Logic of Scientific Discovery. Routledge. ISBN 0-203-99462-0. Stanley, Matthew (2019). Einstein's War: How Relativity Triumphed Amid the Vicious Nationalism of World War I. Dutton. ISBN 978-1-5247-4541-7. == External links == Eclipse 1919, website about the eclipse, the expeditions and centenary events "Eddington's Eclipse and Einstein's Celebrity" Discovery (audio) episode (from BBC World Service) "The man who made Einstein world-famous" (BBC News, 24 May 2019) "Matthew Stanley and Einstein's War". Archived 2020-07-30 at the Wayback Machine (Clarke Center for Human Imagination, UCSD podcast) "100


id: evidence-of-absence-20260505-0
file: data/en.wikipedia.org/wiki/Evidence_of_absence-0.md
category: reference
title: Evidence of absence
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Evidence_of_absence
date_saved: 2026-05-05T09:56:36.622081+00:00
instance: kb-cron
parent: evidence-of-absence-20260505-0
summary:
Evidence of absence is evidence of any kind that suggests something is missing or that it does not exist. What counts as evidence of absence has been a subject of debate between scientists and philosophers. It is often distinguished from absence of evidence. == Overview == Evidence of absence and absence of evidence are similar but distinct concepts. This distinction is captured in the aphorism "Absence of evidence is not evidence of absence." This antimetabole is often attributed to Martin Rees or Carl Sagan, but a version appeared as early as 1888 in a writing by William Wright. In Sagan's words, the expression is a critique of the "impatience with ambiguity" exhibited by appeals to ignorance. Despite what the expression may seem to imply, a lack of evidence can be informative. For example, when testing a new drug, if no harmful effects are observed then this suggests that the drug is safe. This is because, if the drug were harmful, evidence of that fact can be expected to turn up during testing. The expectation of evidence makes its absence significant. As the previous example shows, the difference between evidence that something is absent (e.g., an observation that suggests there were


id: list-of-experiments-in-physics-20260505-0
file: data/en.wikipedia.org/wiki/List_of_experiments_in_physics-0.md
category: reference
title: List of experiments in physics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_experiments_in_physics
date_saved: 2026-05-05T09:56:37.889335+00:00
instance: kb-cron
parent: list-of-experiments-in-physics-20260505-0
summary:
This is a list of notable experiments in physics. The list includes only experiments with Wikipedia articles. For hypothetical experiments, see thought experiment. == Historical experiments == == Articles on several experiments == Bell tests BICEP and Keck Array Coincidence method Discovery of the neutron Large Hadron Collider experiments List of Super Proton Synchrotron experiments Precision tests of QED Tests of special relativity Tests of relativistic energy and momentum Modern searches for Lorentz violation Measurements of neutrino speed Tests of general relativity Experimental testing of time dilation == On-going experiments == Collider Detector at Fermilab China Dark Matter Experiment Cosmic Ray Energetics and Mass Experiment General antiparticle spectrometer GlueX The E and B Experiment VIP2 experiment VITO experiment == See also == List of accelerators in particle physics


id: lady-tasting-tea-20260505-0
file: data/en.wikipedia.org/wiki/Lady_tasting_tea-0.md
category: reference
title: Lady tasting tea
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Lady_tasting_tea
date_saved: 2026-05-05T09:56:39.095339+00:00
instance: kb-cron
parent: lady-tasting-tea-20260505-0
summary:
In the design of experiments in statistics, the lady tasting tea is a randomized experiment devised by Ronald Fisher and reported in his book The Design of Experiments (1935). The experiment is the original exposition of Fisher's notion of a null hypothesis, which is "never proved or established, but is possibly disproved, in the course of experimentation". The example is loosely based on an event in Fisher's life. The woman in question, phycologist Muriel Bristol, claimed to be able to tell whether the tea or the milk was added first to a cup. Her future husband, William Roach, suggested that Fisher give her eight cups, four of each variety, in random order. One could then ask what the probability was for her getting the specific number of cups she identified correct (in fact all eight), but just by chance. Fisher's description is less than 10 pages in length and is notable for its simplicity and completeness regarding terminology, calculations and design of the experiment. The test used was Fisher's exact test. == The experiment == The experiment provides a subject with eight randomly ordered cups of tea – four prepared by pouring milk and then tea, four by pouring tea


id: mesocosm-20260505-0
file: data/en.wikipedia.org/wiki/Mesocosm-0.md
category: reference
title: Mesocosm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mesocosm
date_saved: 2026-05-05T09:56:40.253813+00:00
instance: kb-cron
parent: mesocosm-20260505-0
summary:
A mesocosm (meso- or 'medium' and -cosm 'world') is any outdoor or indoor experimental system that examines the natural environment under controlled conditions. In this way mesocosm studies provide a link between field surveys and highly controlled laboratory experiments. Mesocosms tend to be medium-sized to large (e.g., aquatic mesocosm range: 1 litre (34 US fl oz) to 10,000 litres (2,600 US gal)+) and contain multiple trophic levels of interacting organisms. In contrast to laboratory experiments, mesocosm studies are normally conducted outdoors in order to incorporate natural variation (e.g., diel cycles). Mesocosm studies may be conducted in either an enclosure that is small enough that key variables can be brought under control or by field-collecting key components of the natural environment for further experimentation. In coastal and aquatic ecology, specialized mesocosms can also be designed to reproduce wave climates, allowing experiments on hydrodynamic effects on organisms, sediments, and biogeomorphic processes. Extensive mesocosm studies have been conducted to evaluate how organisms or communities might react to environmental change, through deliberate manipulation of environmental variables, such as increased temperature, carbon dioxide or pH levels. == Advantages == The advantage of mesocosm studies is that environmental gradients of interest (e.g., warming temperatures) can be


id: molten-salt-reactor-experiment-20260505-0
file: data/en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment-0.md
category: reference
title: Molten-Salt Reactor Experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment
date_saved: 2026-05-05T09:56:41.440510+00:00
instance: kb-cron
parent: molten-salt-reactor-experiment-20260505-0
summary:
The Molten-Salt Reactor Experiment (MSRE) was an experimental molten-salt reactor research reactor at the Oak Ridge National Laboratory (ORNL) in Oak Ridge, Tennessee. This technology was researched through the 1960s, the reactor was constructed by 1964, it went critical in 1965, and was operated until 1969. The costs of a cleanup project were estimated at $130 million. Initially designed for 15 MWth, the MSRE was operated at 7.4 MWth because of imprecise nuclear cross section data. It was a test reactor simulating the neutronic "kernel" of a type of inherently safer epithermal thorium breeder reactor called the liquid fluoride thorium reactor. It primarily used two fuels: first uranium-235 and later uranium-233. The latter 233UF4 was the result of breeding from thorium in other reactors. Since this was an engineering test, the large, expensive breeding blanket of thorium salt was omitted in favor of neutron measurements. In the MSRE, the heat from the reactor core was shed via a cooling system using air blown over radiators. It is thought similar reactors could power high-efficiency heat engines such as closed-cycle gas turbines. The MSRE's piping, core vat and structural components were made from Hastelloy-N, and its moderator was a pyrolytic graphite core.


id: molten-salt-reactor-experiment-20260505-1
file: data/en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment-1.md
category: reference
title: Molten-Salt Reactor Experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment
date_saved: 2026-05-05T09:56:41.440510+00:00
instance: kb-cron
parent: molten-salt-reactor-experiment-20260505-0
summary:
=== Structural alloy Hastelloy-N === Hastelloy-N—a low chromium, nickel–molybdenum alloy—was used in the MSRE and proved compatible with the fluoride salts FLiBe and FLiNaK. All metal parts contacting salt were made of Hastelloy-N. The choice of Hastelloy-N for the MSRE was on the basis of the promising results of tests at aircraft nuclear propulsion conditions and the availability of much of the required metallurgical data. Development for the MSRE generated the further data required for ASME code approval. It also included preparation of standards for Hastelloy-N procurement and for component fabrication. Almost 200,000 lb (90,000 kg) in a variety of shapes of material for the MSRE were produced commercially. Requests for bids on component fabrication went to several companies in the nuclear fabrication industry, but all declined to submit lump-sum bids because of lack of experience with the new alloy. Consequently, all major components were fabricated in U.S. Atomic Energy Commission-owned shops at Oak Ridge and Paducah, Kentucky. At the time that design stresses were set for the MSRE, the data that was available indicated that the strength and creep rate of Hastelloy-N were hardly affected by irradiation. After the construction was well along, the stress-rupture life and fracture strain


id: molten-salt-reactor-experiment-20260505-2
file: data/en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment-2.md
category: reference
title: Molten-Salt Reactor Experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment
date_saved: 2026-05-05T09:56:41.440510+00:00
instance: kb-cron
parent: molten-salt-reactor-experiment-20260505-0
summary:
By this time, ample 233U had become available, so the MSRE program was extended to include substitution of 233U for the uranium in the fuel salt, and operation to observe the new nuclear characteristics. Using the on-site processing equipment the flush salt and fuel salt were fluorinated to recover the uranium in them as UF6. 233UF4-LiF eutectic was then added to the carrier salt, and in October 1968, the MSRE became the world's first reactor to operate on 233U. The 233U zero-power experiments and dynamics tests confirmed the predicted neutronic characteristics. An unexpected consequence of processing the salt was that its physical properties were altered slightly so that more than the usual amount of gas was entrained from the fuel pump into the circulating loop. The circulating gas and the power fluctuations that accompanied it were eliminated by operating the fuel pump at slightly lower speed. Operation at high power for several months permitted accurate measurement of the capture-to-fission ratio, for 233U in this reactor, completing the objectives of the 233U operation. In the concluding months of operation, xenon stripping, deposition of fission products, and tritium behavior were investigated. The feasibility of using plutonium in molten-salt reactors was emphasized by


id: molten-salt-reactor-experiment-20260505-3
file: data/en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment-3.md
category: reference
title: Molten-Salt Reactor Experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Molten-Salt_Reactor_Experiment
date_saved: 2026-05-05T09:56:41.440510+00:00
instance: kb-cron
parent: molten-salt-reactor-experiment-20260505-0
summary:
== Decommissioning == After shutdown, the salt was believed to be in long-term safe storage. At low temperatures, radiolysis can free fluorine from the salt. As a countermeasure, the salt was annually reheated to about 302 °F (150 °C) until 1989. But beginning in the mid-1980s, there was concern that radioactivity was migrating through the system, reported by an ORNL employee who was among 125 people working above the reactor, which had not been decontaminated or decommissioned. Department of Energy Oak Ridge Operations Manager Joe Ben LaGrone ordered evacuation of 125 employees, based on findings reported to him inspector William Dan DeFord, P.E. Sampling in 1994 revealed concentrations of uranium that created a potential for a nuclear criticality accident, as well as a potentially dangerous build-up of fluorine gas: the environment above the solidified salt was approximately one atmosphere of fluorine. The ensuing decontamination and decommissioning project was called "the most technically challenging" activity assigned to Bechtel Jacobs under its environmental management contract with the U.S. Department of Energy's Oak Ridge Operations organization. In 2003, decommissioning was expected to be completed in 2009, and the MSRE cleanup project cost estimated at $130 million. Removal of uranium from the salt was


id: oneida-stirpiculture-20260505-0
file: data/en.wikipedia.org/wiki/Oneida_stirpiculture-0.md
category: reference
title: Oneida stirpiculture
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Oneida_stirpiculture
date_saved: 2026-05-05T09:56:43.771376+00:00
instance: kb-cron
parent: oneida-stirpiculture-20260505-0
summary:
The stirpiculture experiment at the Oneida Community was the first positive eugenics experiment in American history, resulting in the planned conception, birth and rearing of 58 children. The experiment lasted from 1869–1879. It was not considered as part of the larger eugenics history because of its radical religious context. The term "stirpiculture" was used by John Humphrey Noyes, founder of the Oneida Community, to refer to his system of eugenics, or the breeding of humans to achieve desired perfections within the species. Noyes derived stirpiculture from the Latin word "stirps", which means "stock, stem, or root" (Carden). It has been claimed that Noyes coined the term two decades before Francis Galton created the term "eugenics". In 1904, Galton claimed that he had first come up with the term and "deliberately changed it for eugenics," a claim supported in print by George Willis Cooke. In his 1883 book Inquiries into Human Faculty and Its Development, Galton noted that his new term "eugenics" was a suitable replacement for the older term "viriculture" that he had invented, suggesting that he had confused the two terms "viriculture" and "stirpiculture." == Origins of the Oneida stirpiculture experiment == Until the late 1860s, John Humphrey Noyes


id: oneida-stirpiculture-20260505-1
file: data/en.wikipedia.org/wiki/Oneida_stirpiculture-1.md
category: reference
title: Oneida stirpiculture
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Oneida_stirpiculture
date_saved: 2026-05-05T09:56:43.771376+00:00
instance: kb-cron
parent: oneida-stirpiculture-20260505-0
summary:
==== The Children's House ==== Once weaned, children were sent to live in the Children's House. In the early days of the community, this "house" was a succession of rooms in the "Middle House". For some time after being weaned, children still slept with their mothers at night. Once they reached a certain age, they were discouraged from sleeping in their mothers' rooms. Still concerned with creating a bond between the child and the community, children would often sleep in the bed of a community member. This member changed periodically so no special attachments could be formed, and thus detract from the overall communal commitment. ==== Values of non-attachment ==== Guidelines were established by the community to help direct parents in establishing an appropriate relationship with their child. Most of these guidelines were an extension of the principles of non-attachment and commitment to the communal ideal. The concern was that an excessive relationship would fail to appropriately teach the child the communal fundamentals of the community. It was acceptable to be attached, as long as this was a general emotion of love and trust to the community, rather than to a particular individual. A mother's excessive attachment to her child


id: organic-moderated-reactor-experiment-20260505-0
file: data/en.wikipedia.org/wiki/Organic_Moderated_Reactor_Experiment-0.md
category: reference
title: Organic Moderated Reactor Experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Organic_Moderated_Reactor_Experiment
date_saved: 2026-05-05T09:56:44.977297+00:00
instance: kb-cron
parent: organic-moderated-reactor-experiment-20260505-0
summary:
The Organic Moderated Reactor Experiment (OMRE) was a 16 MWt experimental organic nuclear reactor that operated at the National Reactor Testing Station from 1957 to 1963 to explore the use of hydrocarbons as coolant, moderator, and reflector materials in power reactor conditions. Such organic fluids are non-corrosive, do not become highly activated under irradiation, and can operate at low pressure and moderate temperature. These characteristics were considered promising towards the goal of achieving economical commercial nuclear power. The information provided by OMRE established the credibility of the Organic nuclear reactor concept and led to the commercial demonstration at the Piqua Nuclear Generating Station. More recently, OMRE has been cited as providing key input and motivation for modern designs of such systems, aiming to help improve performance of new and advanced nuclear power plants towards the goals of climate change mitigation. == Design == The OMRE design efforts began in July 1955. It was originally intended to operate for 1 year. The objectives of the OMRE program were to obtain the following experimental information: Rate of radiation and thermal neutron damage to the hydrocarbon in the reactor Effect of this damage upon the operation of the reactor Suitable methods for ensuring


id: organic-moderated-reactor-experiment-20260505-1
file: data/en.wikipedia.org/wiki/Organic_Moderated_Reactor_Experiment-1.md
category: reference
title: Organic Moderated Reactor Experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Organic_Moderated_Reactor_Experiment
date_saved: 2026-05-05T09:56:44.977297+00:00
instance: kb-cron
parent: organic-moderated-reactor-experiment-20260505-0
summary:
The OMRE first achieved criticality on September 17, 1957, and reached full power at the beginning of February, 1958. The reactor operated in two modes: without the purification system, and with the purification system. Seventeen tests were run with the first OMRE core throughout 1958 with reactor power between 0 and 12 MWt. The first three tests were system check-out tests, covering all major systems. Subsequent tests simulated the conditions expected to be encountered in the Piqua Nuclear Generating Station. Test 4 demonstrated that pyrolitic decomposition rate in external piping was negligible. Tests 5-11 measured the decomposition rate and the effect of radiation damage on coolant-moderator heat-transfer characteristics. Tests 12 and 13 tested the purification system's ability to reduce the concentration of inorganic particulate matter while also reducing the high-boiler concentration from 40% to 8%. Three fuel element failures occurred during first core operation. Two occurred in experimental low-enriched assemblies with finned aluminum cladding due to inadequate coolant filtration, and the third was caused by improper element seating. By the end of the first year, the core had generated 958 MW-day of energy and been in operation for 5,600 hours. An extended shutdown followed to replace the core. Problems with


id: remote-experiment-20260505-0
file: data/en.wikipedia.org/wiki/Remote_experiment-0.md
category: reference
title: Remote experiment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Remote_experiment
date_saved: 2026-05-05T09:56:46.151408+00:00
instance: kb-cron
parent: remote-experiment-20260505-0
summary:
A remote experiment is a real experiment with real laboratory instruments and equipment that can be controlled by a computer through the internet. One or more remote experiments are accessible in remote laboratory. Remotely controlled experiments have become a widespread tool for teaching physics at the university level of education. When executing remote experiments the remote users can change system parameters, observe results in graphical form and/or by video transmission from webcam, and download the experimental results. Sometimes a booking system is available for remote experiments that allows the users to book time for access of remote experiment in advance. User operates remote experiment via graphical user interface. Remote experiments are positively evaluated by the learners. == Advantages of remote experiments == When compared to simulations in virtual laboratories and to experiments in the traditional laboratories, remotely controlled experiments have following advantages: remote experiments can be carried out from anywhere in the world; no time restriction since experiments are available 24 hours a day, 7 days a week; overcoming problems with limited laboratory capacity for numerous students; safe and secure operation of equipment without danger of user's injury; remote experiments can be shared between education institutions as for example in


id: repeated-measures-design-20260505-0
file: data/en.wikipedia.org/wiki/Repeated_measures_design-0.md
category: reference
title: Repeated measures design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Repeated_measures_design
date_saved: 2026-05-05T09:56:47.372113+00:00
instance: kb-cron
parent: repeated-measures-design-20260505-0
summary:
Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed. == Crossover studies == A popular repeated-measures design is the crossover study. A crossover study is a longitudinal study in which subjects receive a sequence of different treatments (or exposures). While crossover studies can be observational studies, many important crossover studies are controlled experiments. Crossover designs are common for experiments in many scientific disciplines, for example psychology, education, pharmaceutical science, and health care, especially medicine. Randomized, controlled, crossover experiments are especially important in health care. In a randomized clinical trial, the subjects are randomly assigned treatments. When such a trial is a repeated measures design, the subjects are randomly assigned to a sequence of treatments. A crossover clinical trial is a repeated-measures design in which each patient is randomly assigned to a sequence of treatments, including at least two treatments (of which one may be a standard treatment or a placebo): Thus each patient crosses over from one treatment to


id: repeated-measures-design-20260505-1
file: data/en.wikipedia.org/wiki/Repeated_measures_design-1.md
category: reference
title: Repeated measures design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Repeated_measures_design
date_saved: 2026-05-05T09:56:47.372113+00:00
instance: kb-cron
parent: repeated-measures-design-20260505-0
summary:
Normality—For each level of the within-subjects factor, the dependent variable must have a normal distribution. Sphericity—Difference scores computed between two levels of a within-subjects factor must have the same variance for the comparison of any two levels. (This assumption only applies if there are more than 2 levels of the independent variable.) Randomness—Cases should be derived from a random sample, and scores from different participants should be independent of each other. The rANOVA also requires that certain multivariate assumptions be met, because a multivariate test is conducted on difference scores. These assumptions include: Multivariate normality—The difference scores are multivariately normally distributed in the population. Randomness—Individual cases should be derived from a random sample, and the difference scores for each participant are independent from those of another participant. === F test === As with other analysis of variance tests, the rANOVA makes use of an F statistic to determine significance. Depending on the number of within-subjects factors and assumption violations, it is necessary to select the most appropriate of three tests: Standard Univariate ANOVA F test—This test is commonly used given only two levels of the within-subjects factor (i.e. time point 1 and time point 2). This test is not recommended


id: resistive-plate-chamber-20260505-0
file: data/en.wikipedia.org/wiki/Resistive_plate_chamber-0.md
category: reference
title: Resistive plate chamber
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Resistive_plate_chamber
date_saved: 2026-05-05T09:56:48.534735+00:00
instance: kb-cron
parent: resistive-plate-chamber-20260505-0
summary:
A Resistive plate chamber (RPC) is a particle detector widely used in high energy physics. They are used for detecting muons in most of the modern experiments including ATLAS, CMS, Belle II and BES III. == References ==


id: room-temperature-20260505-0
file: data/en.wikipedia.org/wiki/Room_temperature-0.md
category: reference
title: Room temperature
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Room_temperature
date_saved: 2026-05-05T09:56:49.758772+00:00
instance: kb-cron
parent: room-temperature-20260505-0
summary:
Room temperature, colloquially, denotes the range of air temperatures most people find comfortable indoors while dressed in typical clothing. Comfortable temperatures can be extended beyond this range depending on humidity, air circulation, and other factors. In certain fields, like science and engineering, and within a particular context, room temperature can mean different agreed-upon ranges. In contrast, ambient temperature is the actual temperature, as measured by a thermometer, of the air (or other medium and surroundings) in any particular place. The ambient temperature (e.g. an unheated room in winter) may be very different from an ideal room temperature. Food and beverages may be served at "room temperature", meaning neither heated nor cooled. == Comfort temperatures == Comfort temperature is interchangeable with neutral temperature in the scientific literature, which can be calculated through regression analysis between thermal sensation votes and indoor temperature. The neutral temperature is the solution of the resulting regression model by setting the thermal sensation vote as zero. The American Heritage Dictionary of the English Language identifies room temperature as around 20–22 °C (68–72 °F; 293–295 K), while the Oxford English Dictionary states that it is "conventionally taken as about 20 °C (68 °F; 293 K)". Ideal room temperature


id: round-hill-generator-20260505-0
file: data/en.wikipedia.org/wiki/Round_Hill_generator-0.md
category: reference
title: Round Hill generator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Round_Hill_generator
date_saved: 2026-05-05T09:56:50.995002+00:00
instance: kb-cron
parent: round-hill-generator-20260505-0
summary:
The Round Hill generator is an experimental high-voltage Van de Graaff generator built at Round Hill, Massachusetts. When constructed in 1933, it was designed as the world's most powerful particle accelerator. The generator is now used at the Boston Museum of Science for educational demonstrations. The instrument was constructed by a Massachusetts Institute of Technology (MIT) team led by physicist Robert J. Van de Graaff, who hoped to be the first scientist to artificially split the atom. They completed construction a year after John Cockroft and Ernest Walton accomplished the feat in 1932. The machine was the forerunner of high-voltage electrostatic particle accelerators built by the High Voltage Engineering Corporation, which Van de Graaff and his student John G. Trump introduced to cancer clinics and nuclear physics labs around the world. Too large to fit in a research lab, the 43-foot-tall generator was assembled in Round Hill's airship hangar. Originally, a technician ran the machine from within one of its metal terminals, which acted as a Faraday cage. It was first demonstrated to the public in November 1933 and dubbed an "electrical Niagara" by the New York Times because of its copious electrical discharges. Coverage in Time, Science, and a


id: round-hill-generator-20260505-1
file: data/en.wikipedia.org/wiki/Round_Hill_generator-1.md
category: reference
title: Round Hill generator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Round_Hill_generator
date_saved: 2026-05-05T09:56:50.995002+00:00
instance: kb-cron
parent: round-hill-generator-20260505-0
summary:
In 1931, Van de Graaff demonstrated a prototype generator at Round Hill. Colonel Green was "delighted" by the generator's spectacular electrical discharges and agreed to Compton's suggestion that a full-scale generator be constructed at the estate. Construction of the large-scale generator began in 1932, with Van de Graaff's equipment and research group moving to Round Hill in August of that year. The high-voltage installation was managed by Lester and Chester van Atta, Edward W. Samson, and Doyle L. Northrup, who operated independently of existing Round Hill research. Needing environmental control, the 43-foot generator was housed in an airship hangar on the estate that had previously been used for a Goodyear dirigible. The machine was first demonstrated to the public on November 28, 1933, generating significant scientific and media attention. The generator produced spectacular lightning discharges, which made it a popular attraction for visitors and potential investors. The team conducted regular demonstrations, during which the machine would shoot huge purple bolts of lightning into the rafters of the hangar, creating a thunderous cracking sound. Though visually arresting, the display showed the operating limits of an air-insulated generator. The arcs of lighting again showed the difficulty of sustaining high voltages without breakdown.


id: round-hill-generator-20260505-2
file: data/en.wikipedia.org/wiki/Round_Hill_generator-2.md
category: reference
title: Round Hill generator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Round_Hill_generator
date_saved: 2026-05-05T09:56:50.995002+00:00
instance: kb-cron
parent: round-hill-generator-20260505-0
summary:
== Technical contributions == The Round Hill generator was primarily designed for nuclear physics research, particularly for the study of atomic nuclei through high-energy particle bombardment. In the early 1930s, this represented the frontier of experimental atomic physics. Ultimately, John Cockcroft and Ernest Walton's 1932 voltage-multiplier circuit produced the first controlled "splitting of the atom." However, electrostatic power offered superior beam control and voltage regulation than contemporaries like the Cockcroft-Walton device, leading to its widespread adoption in nuclear experiments. The Round Hill generator incorporated several technical innovations that advanced the state of high-voltage engineering. The generator featured an improved belt-charging systems that provided more stable operation and better voltage control than previous Van de Graaff designs. The vacuum-insulated accelerating tube prompted advances in vacuum technology. The reinstallation in Cambridge also made several innovations that became standard in subsequent accelerator designs. The generator featured one of the first comprehensive remote control systems for high-voltage equipment to manage radiation exposure concerns. Once re-installed in Cambridge, the installation's vacuum technology achieved pressures as low as 6×10−7 mm Hg, with normal operating pressure of 4×10−6 mm Hg during electron beam operation. The system could also accelerate both positive ions and electrons, though positive ion


id: rye-riptides-20260505-0
file: data/en.wikipedia.org/wiki/Rye_Riptides-0.md
category: reference
title: Rye Riptides
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rye_Riptides
date_saved: 2026-05-05T09:56:52.171847+00:00
instance: kb-cron
parent: rye-riptides-20260505-0
summary:
Rye Riptides is a boat that was made by a 5th grade class in New Hampshire that was released to the Atlantic Ocean in 2020, and spent 462 days at sea before being discovered in Norway in 2022. The boat was built by two science classes at Rye Junior High School in New Hampshire and launched on October 25, 2020; it was found on February 1, 2022, on a small uninhabited island off the larger island of Smøla. == See also == Friendly Floatees == References == == External links == Official site


id: single-subject-design-20260505-0
file: data/en.wikipedia.org/wiki/Single-subject_design-0.md
category: reference
title: Single-subject design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Single-subject_design
date_saved: 2026-05-05T09:56:53.416326+00:00
instance: kb-cron
parent: single-subject-design-20260505-0
summary:
In design of experiments, single-subject curriculum or single-case research design is a research design most often used in applied fields of psychology, education, and human behaviour in which the subject serves as his/her own control, rather than using another individual/group. Researchers use single-subject design because these designs are sensitive to individual organism differences vs group designs which are sensitive to averages of groups. The logic behind single subject designs is 1) Prediction, 2) Verification, and 3) Replication. The baseline data predicts behaviour by affirming the consequent. Verification refers to demonstrating that the baseline responding would have continued had no intervention been implemented. Replication occurs when a previously observed behaviour changed is reproduced. There can be large numbers of subjects in a research study using single-subject design, however—because the subject serves as their own control, this is still a single-subject design. These designs are used primarily to evaluate the effect of a variety of interventions in applied research. == Design standards == === Effect size === Although there are no standards on the specific statistics required for effect size calculation, it is best practice to include an effect size estimate. == Reporting standards == When reporting on findings obtained through single-subject


id: experimental-software-engineering-20260505-0
file: data/en.wikipedia.org/wiki/Experimental_software_engineering-0.md
category: reference
title: Experimental software engineering
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Experimental_software_engineering
date_saved: 2026-05-05T09:56:54.579784+00:00
instance: kb-cron
parent: experimental-software-engineering-20260505-0
summary:
Experimental software engineering involves running experiments on the processes and procedures involved in the creation of software systems, with the intent that the data be used as the basis of theories about the processes involved in software engineering (theory backed by data is a fundamental tenet of the scientific method). A number of research groups primarily use empirical and experimental techniques. The term empirical software engineering emphasizes the use of empirical studies of all kinds to accumulate knowledge. Methods used include experiments, case studies, surveys, and using whatever data is available. == Empirical software engineering research == In a keynote at the International Symposium on Empirical Software Engineering and Measurement Prof. Wohlin recommended ten commitments that the research community should follow to increase the relevance and impact of empirical software engineering research. However, at the same conference Dr. Ali effectively argued that solely following these will not be enough and we need to do more than just show the evidence substantiating the claimed benefits of our interventions but instead what is required for practical relevance and potential impact is the evidence for cost-effectiveness. The International Software Engineering Research Network (ISERN) is a global community of research groups who are active


id: timeline-of-snowflake-research-20260505-0
file: data/en.wikipedia.org/wiki/Timeline_of_snowflake_research-0.md
category: reference
title: Timeline of snowflake research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Timeline_of_snowflake_research
date_saved: 2026-05-05T09:56:55.831024+00:00
instance: kb-cron
parent: timeline-of-snowflake-research-20260505-0
summary:
The hexagonal snowflake, a crystalline formation of ice, has intrigued people throughout history. This is a chronology of interest and research into snowflakes. Artists, philosophers, and scientists have wondered at their shape, recorded them by hand or in photographs, and attempted to recreate hexagonal snowflakes. Wilson Alwyn Bentley (February 9, 1865 – December 23, 1931), also known as Snowflake Bentley, was an American meteorologist and photographer, who was the first known person to take detailed photographs of snowflakes and record their features.[1] He perfected a process of catching flakes on black velvet in such a way that their images could be captured before they either melted or sublimated. == Chronological list == === BC to 1900 === 150 BCE or 135 BCE - Han Ying (韓嬰) compiled the anthology Han shi waizhuan, which includes a passage that contrasts the pentagonal symmetry of flowers with the hexagonal symmetry of snow. This is discussed further in the Imperial Readings of the Taiping Era. 1250 - Albertus Magnus offers what is believed to be the oldest detailed description of snow. 1555 - Olaus Magnus publishes the earliest snowflake diagrams in Historia de gentibus septentrionalibus. 1611 - Johannes Kepler, in Strenaseu De Nive Sexangula,


id: wet-lab-20260505-0
file: data/en.wikipedia.org/wiki/Wet_lab-0.md
category: reference
title: Wet lab
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Wet_lab
date_saved: 2026-05-05T09:57:11.971557+00:00
instance: kb-cron
parent: wet-lab-20260505-0
summary:
A wet lab, or experimental lab, is a type of laboratory where it is necessary to handle various types of chemicals and potential "wet" hazards, so the room has to be carefully designed, constructed, and controlled to avoid spillage and contamination. A dry lab might have large experimental equipment but minimal chemicals, or instruments for analyzing data produced elsewhere. == Overview == A wet lab is a type of laboratory in which a wide range of experiments are performed, for example, characterizing of enzymes in biology, titration in chemistry, diffraction of light in physics, etc. - all of which may sometimes involve dealing with hazardous substances. Due to the nature of these experiments, the proper appropriate arrangement of safety equipment are of great importance. The researchers (the occupants) are required to know basic laboratory techniques including safety procedures and techniques related to the experiments that they perform. == Laboratory design == At the present, lab design tends to focus on increasing the interactions between researchers through the use of open plans, allowing the space and opportunity for researchers to exchange ideas, share equipment, and share storage space; increasing productivity and efficiency of experiments. This style of design has been proposed


id: widefield-askap-l-band-legacy-all-sky-blind-survey-20260505-0
file: data/en.wikipedia.org/wiki/Widefield_ASKAP_L-Band_Legacy_All-Sky_Blind_Survey-0.md
category: reference
title: Widefield ASKAP L-Band Legacy All-Sky Blind Survey
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Widefield_ASKAP_L-Band_Legacy_All-Sky_Blind_Survey
date_saved: 2026-05-05T09:57:13.153533+00:00
instance: kb-cron
parent: widefield-askap-l-band-legacy-all-sky-blind-survey-20260505-0
summary:
The Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) is a next-generation survey of the 21 cm radio emission from neutral hydrogen (HI) in the Local Universe. It is hosted by the Australian Square Kilometer Array Pathfinder (ASKAP) telescope, WALLABY will survey three-quarters of the sky over a Declination range −90° to +30° to a redshift of 0.26. It will have an angular resolution of 30 arcsec and a sensitivity of 1.6 mJy/beam in each 4 km/s channel. WALLABY is expected to detect about 500,000 galaxies with a mean redshift of 0.05, at a mean distance of about 200 Mpc. The scientific goals of WALLABY include: a census of gas-rich galaxies in the vicinity of the Local Group; a study of the HI properties of galaxies, groups and clusters, including the influence of the environment on galaxy evolution; == History == The WALLABY project was proposed in 2009 by a team led by B. S. Koribalski and L. Staveley-Smith. It was ranked by ASKAP in the top two of ten Survey Science projects, with Koribalski and Staveley-Smith the principal investigators. Koribalski stepped down in 2019. Currently, Lister Staveley-Smith is the Principal Investigator, Karen Lee-Waddell is the project scientist, and Tobias


id: write-once-read-forever-20260505-0
file: data/en.wikipedia.org/wiki/Write_Once_Read_Forever-0.md
category: reference
title: Write Once Read Forever
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Write_Once_Read_Forever
date_saved: 2026-05-05T09:57:14.332179+00:00
instance: kb-cron
parent: write-once-read-forever-20260505-0
summary:
Write Once Read Forever (WORF) is a data storage method which allows users to write data once and allows storage of the users data without ever being refreshed. This differs from common digital storage techniques such as drives that need to be re-written often to prevent loss or corruption of data. WORF was tested on the International Space Station in 2019. == Method == WORF uses a data storage mechanism based on silver halide, which after substantial testing has been determined to last for more than a century under conventional ambient environmental conditions. WORF digital data is stored as microscopic, metallic, interference-created standing waves (representing narrowband ‟colors” ) embedded in a modern, super-resolution, dye-free, photosensitive emulsion. Wavelengths encode multiple superimposed states allowing complex data permutations to be stored per data region. Permutations enable extremely high data density to be stored on WORF media. Multi-state data architecture within each domain also enhances data integrity, error-checking, and accelerates parallel writing and reading for the entire media module. Once data is written to WORF, energy is needed only for reading—no periodic refresh is necessary, and data is both immutable and truly permanent. Human readable text and images are embedded in the WORF module


id: heuristic-engineering-20260505-0
file: data/en.wikipedia.org/wiki/Heuristic_(engineering)-0.md
category: reference
title: Heuristic (engineering)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(engineering)
date_saved: 2026-05-05T09:57:15.882007+00:00
instance: kb-cron
parent: heuristic-engineering-20260505-0
summary:
In engineering, heuristics are experience-based methods used to reduce the need for calculations pertaining to equipment size, performance, or operating conditions. Heuristics are fallible and do not guarantee a correct solution. It is important to understand their limitations when applying them to different equipment and processes. Though heuristics are limited, they may be of value. This is because they offer time-saving approximations in preliminary process design. Problem solving methods are intrinsic to forensic engineering methods, where failures are analysed for the root cause or causes. Only when failures have been investigated with conclusive results can remedial action be taken with confidence. == Examples == === Storage Vessels === These heuristics were taken from Turton's "Analysis, Synthesis, and Design of Chemical Processes". Use vertical tanks on legs when the tank is less than 3.8 m3. Use horizontal tanks on concrete supports when the tank is between 3.8 and 38 m3, Use vertical tanks on concrete pads when the tank is beyond 38 m3, Liquids subject to breathing losses may be stored in tanks with floating or expansion roofs for conservation. Freeboard is 15% below 1.9 m3 and 10% above 1.9 m3. Thirty-day capacity often is specified for raw materials and products,


id: admissible-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Admissible_heuristic-0.md
category: reference
title: Admissible heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Admissible_heuristic
date_saved: 2026-05-05T09:57:17.054508+00:00
instance: kb-cron
parent: admissible-heuristic-20260505-0
summary:
In computer science, specifically in algorithms related to pathfinding, a heuristic function is said to be admissible if it never overestimates the cost of reaching the goal, i.e. the cost it estimates to reach the goal is not higher than the lowest possible cost from the current point in the path. In other words, it should act as a lower bound. It is related to the concept of consistent heuristics. While all consistent heuristics are admissible, not all admissible heuristics are consistent. == Search algorithms == An admissible heuristic is used to estimate the cost of reaching the goal state in an informed search algorithm. In order for a heuristic to be admissible to the search problem, the estimated cost must always be lower than or equal to the actual cost of reaching the goal state. The search algorithm uses the admissible heuristic to find an estimated optimal path to the goal state from the current node. For example, in A* search the evaluation function (where n {\displaystyle n} is the current node) is: f ( n ) = g ( n ) + h ( n ) {\displaystyle f(n)=g(n)+h(n)} where f ( n ) {\displaystyle f(n)} = the evaluation


id: affect-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Affect_heuristic-0.md
category: reference
title: Affect heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Affect_heuristic
date_saved: 2026-05-05T09:57:18.202032+00:00
instance: kb-cron
parent: affect-heuristic-20260505-0
summary:
The affect heuristic is a heuristic, a mental shortcut that allows people to make decisions and solve problems quickly and efficiently, in which current emotion—fear, pleasure, surprise, etc.—influences decisions. In other words, it is a type of heuristic in which emotional response, or "affect" in psychological terms, plays a lead role. It is a subconscious process that shortens the decision-making process and allows people to function without having to complete an extensive search for information. It is shorter in duration than a mood, occurring rapidly and involuntarily in response to a stimulus. Reading the words "lung cancer" usually generates an affect of dread, while reading the words "mother's love" usually generates a feeling of affection and comfort. The affect heuristic is typically used while judging the risks and benefits of something, depending on the positive or negative feelings that people associate with a stimulus. It is the equivalent of "going with your gut". If their feelings towards an activity are positive, then people are more likely to judge the risks as low and the benefits high. On the other hand, if their feelings towards an activity are negative, they are more likely to perceive the risks as high and benefits


id: affect-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Affect_heuristic-1.md
category: reference
title: Affect heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Affect_heuristic
date_saved: 2026-05-05T09:57:18.202032+00:00
instance: kb-cron
parent: affect-heuristic-20260505-0
summary:
=== Subliminal affective response === The cause of affect does not necessarily have to be consciously perceived. A study conducted by Winkielman, Zajonc and Schwarz (1997) demonstrated the speed at which an affective reaction can influence judgements. To do this they used a subliminal priming paradigm where participants were "primed" through exposure to either a smiling face, a frowning face, or a neutral polygon presented at about 1⁄250 of a second. This was considered an amount of time where the nature of the stimuli could not be recalled. Participants were then exposed to an ideograph (e.g. a Chinese character) for two seconds and asked to rate the ideograph on a scale of liking. Researchers found that participants preferred the ideograph preceded with a smiling face as opposed to those preceded by a frowning face or neutral polygon despite the fact that the smiling face was only shown for 1⁄250 of a second. The same experiment demonstrated the persistence of initial affect. During a second session, participations were primed with the same characters, but these characters were preceded by a different face that they were not previously exposed to (e.g. those previously exposed to the smiling face were now exposed to


id: affect-heuristic-20260505-2
file: data/en.wikipedia.org/wiki/Affect_heuristic-2.md
category: reference
title: Affect heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Affect_heuristic
date_saved: 2026-05-05T09:57:18.202032+00:00
instance: kb-cron
parent: affect-heuristic-20260505-0
summary:
=== Fear appeals === Health campaigns often use “fear appeals” to grab the attention of their audience. Fear appeals are a type of advertising that specifically uses methods of creating anxiety in the consumer which results in the consumer wanting to cure this fear by purchasing the product. In a study by Averbeck, Jones, and Robertson (2011), researchers look at how prior knowledge influences one's response to fear appeals. Surveys were distributed which manipulated prior knowledge as low or high and two different topics: sleep deprivation or spinal meningitis. Various scale were used to test how prior knowledge affects certain health-related issues. Researchers found that individuals who had prior knowledge in a certain subject exhibited less fear and were least likely to fall prey to the affect heuristic as opposed to individuals that did not have prior knowledge who exhibited more fear and were more likely to fall prey. Another example of how fear appeals are used in marketing today is through the findings presented in the experiment by Schmitt and Blass (2008). They produced two versions of an anti-smoking film. One contained high fear arousal and one did not. Out of the participants (46 non-smoking students and 5 smoking


id: affect-heuristic-20260505-3
file: data/en.wikipedia.org/wiki/Affect_heuristic-3.md
category: reference
title: Affect heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Affect_heuristic
date_saved: 2026-05-05T09:57:18.202032+00:00
instance: kb-cron
parent: affect-heuristic-20260505-0
summary:
=== Smiling === Research has been done on how smiling can cause affective responses and thus influence our opinions of others. An experiment by LaFrance and Hecht (1995) investigated whether a smiling target would elicit more leniency than those that do not. Participants judged a case of potential academic misconduct and were asked to rate a list of subjects. Materials included photos of a female target either showing a neutral expression, felt smile, false smile, or miserable smile. Researchers found that the student pictured as smiling received less punishment than did the student who did not smile despite the fact that the smiling student was not seen as less guilty. They did not find a significant difference between the different smiles. Smiling students were also rated as more trustworthy, honest, genuine, good, obedient, sincere, and admirable compared to the student that did not smile. To the previous studies evidence, there is further evidence on the effect of smiling on a person’s perception. They contain it in the experiment by Delevati and Cesar (1994). Brazilian undergraduates perceived a slide of a male and female person. Smiling faces were portrayed and non-smiling faces were portrayed. The participants used 12 different adjectives to


id: anchoring-effect-20260505-0
file: data/en.wikipedia.org/wiki/Anchoring_effect-0.md
category: reference
title: Anchoring effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anchoring_effect
date_saved: 2026-05-05T09:57:19.378582+00:00
instance: kb-cron
parent: anchoring-effect-20260505-0
summary:
The anchoring effect is a psychological phenomenon in which an individual's judgments or decisions are influenced by a reference point or "anchor" which can be completely irrelevant. The original description of the anchoring effect came from psychophysics. When judging stimuli along a continuum, it was noticed that the first and last stimuli were used to compare the other stimuli (this is also referred to as "end anchoring"). This concept was notably formalized in behavioral economics by Amos Tversky and Daniel Kahneman. In their seminal 1974 work, they described anchoring as a heuristic used to make estimates under uncertainty. Both numeric and non-numeric anchoring have been reported through research. In numeric anchoring, once the value of the anchor is set, subsequent arguments, estimates, etc. made by an individual may change from what they would have otherwise been without the anchor. For example, an individual may be more likely to purchase a car if it is placed alongside a more expensive model (the anchor). Non-numeric anchoring has been observed in physical judgments involving length, weight, and volume. == Experimental findings == The anchoring and adjustment heuristic was first theorized by Amos Tversky and Daniel Kahneman. In one of their first studies, participants


id: anchoring-effect-20260505-1
file: data/en.wikipedia.org/wiki/Anchoring_effect-1.md
category: reference
title: Anchoring effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anchoring_effect
date_saved: 2026-05-05T09:57:19.378582+00:00
instance: kb-cron
parent: anchoring-effect-20260505-0
summary:
=== Durability of anchoring === Anchoring effects are also shown to remain adequately present given the accessibility of knowledge pertaining to the target. This, in turn, suggests that despite a delay in judgement towards a target, the extent of anchoring effects have seen to remain unmitigated within a given time period. A series of three experiments were conducted to test the longevity of anchoring effects. It was observed that despite a delay of one week being introduced for half the sample population of each experiment, similar results of immediate judgement and delayed judgement of the target were achieved. The experiments concluded that external information experienced within the delayed judgement period shows little influence relative to self-generated anchors even with commonly encountered targets (temperature) used in one of the experiments, showing that anchoring effects may precede priming in duration especially when the anchoring effects were formed during the task. Further research to conclude an effect that is effectively retained over a substantial period of time has proven inconsistent. === Pervasiveness across contexts === One notable characteristic of the anchoring effect is its pervasiveness across diverse judgment scenarios. Furnham and Boo (2011) highlight that anchoring occurs not only in abstract estimation tasks


id: anchoring-effect-20260505-2
file: data/en.wikipedia.org/wiki/Anchoring_effect-2.md
category: reference
title: Anchoring effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anchoring_effect
date_saved: 2026-05-05T09:57:19.378582+00:00
instance: kb-cron
parent: anchoring-effect-20260505-0
summary:
=== Anchoring-and-adjusting === The most prevalent explanation of the anchoring effect is the argument originally made by Tversky and Kahneman, termed anchoring-and-adjusting. Based on this theory, individuals set an anchor according to available information, whether it is provided or individuals already have an anchor in mind, and use this anchor as a point of reference to adjust their answers. This theory explains inaccuracy in guessing by suggesting that people adjust insufficiently, rendering their final guess closer to the anchors. This phenomenon was further investigated in other studies and used as an explanation for biases such as hindsight bias and egocentric bias. For instance, when asked to guess the price of a drink in a coffee shop, individuals often look for the price of other drinks or recall the price of similar drinks at other stores, and base their answer on the anchor that they set. Specifically, the original study found that by simply providing an arbitrary anchor to each group, people provided significantly different responses, suggesting that their answers were generated through anchoring and adjusting. In addition, this finding suggests that individuals are gullible when setting an anchor, and almost automatically begin the anchoring-and-adjusting process. On the other hand, Epley


id: anchoring-effect-20260505-3
file: data/en.wikipedia.org/wiki/Anchoring_effect-3.md
category: reference
title: Anchoring effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anchoring_effect
date_saved: 2026-05-05T09:57:19.378582+00:00
instance: kb-cron
parent: anchoring-effect-20260505-0
summary:
=== Attitude change === On the contrary of the two previous theories, the attitude change view suggests that individuals' attitude towards an anchor, specifically provided anchors, can heavily affect the extent of the anchoring effect. Recall that individuals often seek to confirm their hypothesis rather than objectively evaluating all information. When individuals disagree with the provided anchor, they will selectively seek evidence that supports their own attitudes instead of the provided anchor, resulting in an unobserved anchoring effect. This theory highlights the idea that the distinct anchoring effect observed with self-generated and provided anchors roots from individual attitude (i.e., does the individual believe in the anchor) rather than the anchors themselves, supporting the integrative theory proposed by Simmons and colleagues. Furthermore, supporters of this view have argued that attitude change is an alternative explanation of the anchoring effect. Providing an anchor generates favorable attitudes in individuals toward the anchor, biasing consequent judgments. === Extremeness aversion === Extremeness aversion is a robust phenomenon where people try to avoid the extremes during decision-making, such as selecting the middle options more often than other extreme options and avoiding reporting the maximum or minimum on a Likert scale. This desire to avoid extremes is


id: anchoring-effect-20260505-4
file: data/en.wikipedia.org/wiki/Anchoring_effect-4.md
category: reference
title: Anchoring effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anchoring_effect
date_saved: 2026-05-05T09:57:19.378582+00:00
instance: kb-cron
parent: anchoring-effect-20260505-0
summary:
=== Personal experience === Early research found that experts (those with high knowledge, experience, or expertise in some field) were more resistant to the anchoring effect. However, anchoring happens unconsciously which means that unless someone who is knowledgeable is warned prior, they are still susceptible to anchoring. Since then, however, numerous studies have demonstrated that while experience can sometimes reduce the effect, even experts are susceptible to anchoring. In a study concerning the effects of anchoring on judicial decisions, researchers found that even experienced legal professionals were affected by anchoring. This remained true even when the anchors provided were arbitrary and unrelated to the case in question. Also, this relates to goal setting, where more experienced individuals will set goals based on their past experiences which consequently affects end results in negotiations. Expertise is typically defined as domain-specific knowledge and experience. In a study using price estimation of cars, it was found that relevant knowledge positively influenced anchoring. Expertise in cognitive bias is related to experience however the two are not exclusively exhaustive. In a study using stock return estimates, it was found that expertise decreases behavioural bias significantly. It was found that other factors like cognitive ability and experience


id: anchoring-effect-20260505-5
file: data/en.wikipedia.org/wiki/Anchoring_effect-5.md
category: reference
title: Anchoring effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anchoring_effect
date_saved: 2026-05-05T09:57:19.378582+00:00
instance: kb-cron
parent: anchoring-effect-20260505-0
summary:
=== Anchoring in negotiation === In the negotiation process anchoring serves to determine an accepted starting point for the subsequent negotiations. As soon as one side states their first price offer, the (subjective) anchor is set. The counterbid (counter-anchor) is the second-anchor. In addition to the initial research conducted by Tversky and Kahneman, multiple other studies have shown that anchoring can greatly influence the estimated value of an object. For instance, although negotiators can generally appraise an offer based on multiple characteristics, studies have shown that they tend to focus on only one aspect. In this way, a deliberate starting point can strongly affect the range of possible counteroffers. The process of offer and counteroffer results in a mutually beneficial arrangement. However, multiple studies have shown that initial offers have a stronger influence on the outcome of negotiations than subsequent counteroffers. An example of the power of anchoring has been conducted during the Strategic Negotiation Process Workshops. During the workshop, a group of participants is divided into two sections: buyers and sellers. Each side receives identical information about the other party before going into a one-on-one negotiation. Following this exercise, both sides debrief about their experiences. The results show that


id: availability-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Availability_heuristic-0.md
category: reference
title: Availability heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Availability_heuristic
date_saved: 2026-05-05T09:57:20.549400+00:00
instance: kb-cron
parent: availability-heuristic-20260505-0
summary:
The availability heuristic, also known as availability bias, is a mental shortcut that relies on immediate examples that come to a given person's mind when evaluating a specific topic, concept, method, or decision. This heuristic, operating on the notion that, if something can be quickly recalled, it must be important, or at least more important than alternative solutions not as readily recalled, is inherently biased toward recently acquired information. The mental availability of an action's consequences is positively related to those consequences' perceived magnitude. In other words, the easier it is to recall the consequences of something, the greater those consequences are often perceived to be. Most notably, people often rely on the content of their recall if its implications are not called into question by the difficulty they have in recalling it. == Overview and history == In the late 1960s and early 1970s, Amos Tversky and Daniel Kahneman began work on a series of papers examining "heuristic and biases" used in judgment under uncertainty. Prior to that, the predominant view in the field of human judgment was that humans are rational actors. Kahneman and Tversky explained that judgment under uncertainty often relies on a limited number of simplifying


id: availability-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Availability_heuristic-1.md
category: reference
title: Availability heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Availability_heuristic
date_saved: 2026-05-05T09:57:20.549400+00:00
instance: kb-cron
parent: availability-heuristic-20260505-0
summary:
When participants were shown two visual structures and asked to pick the structure that had more paths, participants saw more paths in the structure that had more obvious available paths. In the structure that participants chose, there were more columns and shorter obvious paths, making it more available to them. When participants were asked to complete tasks involving estimation, they would often underestimate the end result. Participants were basing their final estimation on a quick first impression of the problem. Participants particularly struggled when the problems consisted of multiple steps. This occurred because participants were basing their estimation on an initial impression. Participants failed to account for the high rate of growth in the later steps due to the impression they formed in the initial steps. This was shown again in a task that asked participants to estimate the answer to a multiplication task, in which the numbers were presented as either 1x2x3x4x5x6x7x8 or 8x7x6x5x4x3x2x1. Participants who were presented the equation with the larger numbers first (8x7x6...), estimated a significantly higher result than participants with the lower numbers first (1x2x3...). Participants were given a short amount of time to make the estimation, thus participants based their estimates off of what


id: availability-heuristic-20260505-2
file: data/en.wikipedia.org/wiki/Availability_heuristic-2.md
category: reference
title: Availability heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Availability_heuristic
date_saved: 2026-05-05T09:57:20.549400+00:00
instance: kb-cron
parent: availability-heuristic-20260505-0
summary:
=== Media === After seeing news stories about child abductions, people may judge that the likelihood of this event is greater. Media coverage can help fuel a person's example bias with widespread and extensive coverage of unusual events, such as homicide or airline accidents, and less coverage of more routine, less sensational events, such as common diseases or car accidents. Long term consumption of this media will skew the consumer's reality and influence their attitudes and emotions. This is referred to as cultivation theory, which aligns with availability bias: frequent exposure to similar news stories causes consumers to inflate their sense of how likely these dangers are. For example, when asked to rate the probability of a variety of causes of death, people tend to rate "newsworthy" events as more likely because they can more readily recall an example from memory. Moreover, unusual and vivid events like homicides, shark attacks, or lightning are more often reported in mass media than common and un-sensational causes of death like common diseases. For example, many people think that the likelihood of dying from shark attacks is greater than that of dying from being hit by falling airplane parts when more people actually die


id: availability-heuristic-20260505-3
file: data/en.wikipedia.org/wiki/Availability_heuristic-3.md
category: reference
title: Availability heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Availability_heuristic
date_saved: 2026-05-05T09:57:20.549400+00:00
instance: kb-cron
parent: availability-heuristic-20260505-0
summary:
Outcome Availability – availability of positive and negative investment outcomes, and Risk Availability – availability of financial risk. On days of substantial stock market moves, abnormal stock price reactions to upgrades are weaker, than those to downgrades. These availability effects are still significant even after controlling for event-specific and company-specific factors. Similarly, research has pointed out that under the availability heuristic, humans are not reliable because they assess probabilities by giving more weight to current or easily recalled information instead of processing all relevant information. Since information regarding the current state of the economy is readily available, researchers attempted to expose the properties of business cycles to predict the availability bias in analysts' growth forecasts. They showed the availability heuristic to play a role in analysis of forecasts and influence investments because of this. In effect, investors are using the availability heuristic to make decisions and subsequently, may be obstructing their own investment success. An investor's lingering perceptions of a dire market environment may be causing them to view investment opportunities through an overly negative lens, making it less appealing to consider taking on investment risk, no matter how small the returns on perceived "safe" investments. To illustrate, Franklin Templeton's


id: availability-heuristic-20260505-4
file: data/en.wikipedia.org/wiki/Availability_heuristic-4.md
category: reference
title: Availability heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Availability_heuristic
date_saved: 2026-05-05T09:57:20.549400+00:00
instance: kb-cron
parent: availability-heuristic-20260505-0
summary:
=== Criminal justice === The media usually focuses on violent or extreme cases, which are more readily available in the public's mind. This may come into play when it is time for the judicial system to evaluate and determine the proper punishment for a crime. In one study, respondents rated how much they agreed with hypothetical laws and policies such as "Would you support a law that required all offenders convicted of unarmed muggings to serve a minimum prison term of two years?" Participants then read cases and rated each case on several questions about punishment. As hypothesized, respondents recalled more easily from long-term memory stories that contain severe harm, which seemed to influence their sentencing choices to make them push for harsher punishments. This can be eliminated by adding high concrete or high contextually distinct details into the crime stories about less severe injuries. A similar study asked jurors and college students to choose sentences on four severe criminal cases in which prison was a possible but not an inevitable sentencing outcome. Respondents answering questions about court performance on a public opinion formulated a picture of what the courts do and then evaluated the appropriateness of that behavior. Respondents


id: availability-heuristic-20260505-5
file: data/en.wikipedia.org/wiki/Availability_heuristic-5.md
category: reference
title: Availability heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Availability_heuristic
date_saved: 2026-05-05T09:57:20.549400+00:00
instance: kb-cron
parent: availability-heuristic-20260505-0
summary:
=== Judging frequency and probability === In general, availability is correlated with ecological frequency, but it is also affected by other factors. Consequently, the reliance on the availability heuristic leads to systematic biases. Such biases are demonstrated in the judged frequency of classes of words, of combinatoric outcomes, and of repeated events. The phenomenon of illusory correlation is explained as an availability bias. In the original Tversky and Kahneman (1973) research, three major factors that are discussed are the frequency of repetition, frequency of co-occurrence, and illusory correlation. The use of frequency of repetition aids in the retrieval of relevant instances. The idea behind this phenomenon is that the more an instance is repeated within a category or list, the stronger the link between the two instances becomes. Individuals then use the strong association between the instances to determine the frequency of an instance. Consequently, the association between the category or list and the specific instance often influences frequency judgement. Frequency of co-occurrence strongly relates to Frequency of repetition, such that the more an item-pair is repeated, the stronger the association between the two items becomes, leading to a bias when estimating the frequency of co-occurrence. Due to the phenomena


id: baconian-method-20260505-0
file: data/en.wikipedia.org/wiki/Baconian_method-0.md
category: reference
title: Baconian method
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Baconian_method
date_saved: 2026-05-05T09:57:21.768116+00:00
instance: kb-cron
parent: baconian-method-20260505-0
summary:
The Baconian method is the investigative method developed by Francis Bacon, one of the founders of modern science, and thus a first formulation of a modern scientific method. The method was put forward in Bacon's book Novum Organum (1620), or 'New Method', to replace the old methods put forward in Aristotle's Organon. It influenced the early modern rejection of medieval Aristotelianism. == Description in the Novum Organum == === Bacon's view of induction === Bacon's method is an example of the application of inductive reasoning. However, Bacon's method of induction is much more complex than the essential inductive process of making generalisations from observations. Bacon's method begins with description of the requirements for making the careful, systematic observations necessary to produce quality facts. He then proceeds to use induction, the ability to generalise from a set of facts to one or more axioms. However, he stresses the necessity of not generalising beyond what the facts truly demonstrate. The next step may be to gather additional data, or the researcher may use existing data and the new axioms to establish additional axioms. Specific types of facts can be particularly useful, such as negative instances, exceptional instances and data from experiments. The


id: baconian-method-20260505-1
file: data/en.wikipedia.org/wiki/Baconian_method-1.md
category: reference
title: Baconian method
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Baconian_method
date_saved: 2026-05-05T09:57:21.768116+00:00
instance: kb-cron
parent: baconian-method-20260505-0
summary:
== Natural history == The Natural History of Pliny the Elder was a classical Roman encyclopedia work. Induction, for Bacon's followers, meant a type of rigour applied to factual matters. Reasoning should not be applied in plain fashion to just any collection of examples, an approach identified as "Plinian". In considering natural facts, a fuller survey was required to form a basis for going further. Bacon made it clear he was looking for more than "a botany" with discursive accretions. In concrete terms, the cabinet of curiosities, exemplifying the Plinian approach, was to be upgraded from a source of wonderment to a challenge to science. The main source in Bacon's works for the approach was his Sylva Sylvarum, and it suggested a more systematic collection of data in the search for causal explanations. Underlying the method, as applied in this context, are therefore the "tables of natural history" and the ways in which they are to be constructed. Bacon's background in the common law has been proposed as a source for this concept of investigation. As a general intellectual programme, Bacon's ideas on "natural history" have been seen as a broad influence on British writers later in the 17th century,


id: cognitive-inertia-20260505-0
file: data/en.wikipedia.org/wiki/Cognitive_inertia-0.md
category: reference
title: Cognitive inertia
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cognitive_inertia
date_saved: 2026-05-05T09:57:22.921691+00:00
instance: kb-cron
parent: cognitive-inertia-20260505-0
summary:
Cognitive inertia is the tendency – for a particular orientation in an individual's thinking about a matter, belief, or strategy – to resist change. Clinical and neuroscientific literature often describes it as a lack of motivation to generate cognitive processes needed to attend to a matter or problem. The physics term "inertia" emphasizes resistance to change in a mode of cognitive processing that has been used for a substantial time. Commonly confused with belief perseverance, cognitive inertia is perseverance in an interpretation of information, not perseverance in the belief itself. Cognitive inertia has been causally implicated in disregard of impending threats to one's health or environment, in enduring political values, and in deficits in task switching. Interest in the phenomenon was taken up by economic and industrial psychologists primarily to explain resistance to change in brand loyalty, in group brainstorming, and in business strategizing. In a clinical setting, cognitive inertia has been used as a diagnostic tool for neurodegenerative diseases, depression, and anxiety. Critics have commented that the term "cognitive inertia" oversimplifies resistant thought processes and suggest a more integrative approach involving motivation, emotion, and developmental factors. == History and methods == === Early history === The idea of cognitive


id: cognitive-inertia-20260505-1
file: data/en.wikipedia.org/wiki/Cognitive_inertia-1.md
category: reference
title: Cognitive inertia
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cognitive_inertia
date_saved: 2026-05-05T09:57:22.921691+00:00
instance: kb-cron
parent: cognitive-inertia-20260505-0
summary:
where p(a) and p(b) refer to the initial opinions, before the communication induced changes. This formula was used by McGuire to show that the effect of a persuasive message on a related, but unmentioned, topic (d) took time to sink in. The assumption was that topic d was predicated on issues a and b, similar to issue c, so if the individual agreed with issue c then so too should they agree with issue d. However, in McGuire's initial study immediate measurement on issue d, after agreement on issues a, b and c, had only shifted half the amount that would be expected to be logically consistent. Follow-up a week later showed that shift in opinion on issue d had shifted enough to be logically consistent with issues a, b, and c, which not only supported the theory of cognitive consistency, but also the initial hurdle of cognitive inertia. The model was based on probability to account for the idea that individuals do not necessarily assume every issue is 100% likely to happen, but instead there is a likelihood of an issue occurring and the individual's opinion on that likelihood will rest on the likelihood of other interrelated issues. ==


id: cognitive-inertia-20260505-2
file: data/en.wikipedia.org/wiki/Cognitive_inertia-2.md
category: reference
title: Cognitive inertia
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cognitive_inertia
date_saved: 2026-05-05T09:57:22.921691+00:00
instance: kb-cron
parent: cognitive-inertia-20260505-0
summary:
=== Brand loyalty === Gaining and retaining new customers is essential to whether a business succeeds early on. To assess a service, product, or likelihood of customer retention, many companies will invite their customers to complete satisfaction surveys immediately after purchasing a product or service. However, unless the satisfaction survey is completed immediately after the point of purchase, the customer response is often based on an existing mindset about the company, not the actual quality of experience. Unless the product or service is extremely negative or positive, cognitive inertia related to how the customer feels about the company will not be inhibited, even when the product or service is substandard. These satisfaction surveys can lack the information businesses need to improve a service or product that will allow them to survive against the competition. === Brainstorming === Cognitive inertia plays a role in why a lack of ideas is generated during group brainstorming sessions. Individuals in a group will often follow an idea trajectory, in which they continue to narrow in on ideas based on the very first idea proposed in the brainstorming session. This idea trajectory inhibits the creation of new ideas central to the group's initial formation. In


id: cognitive-inertia-20260505-3
file: data/en.wikipedia.org/wiki/Cognitive_inertia-3.md
category: reference
title: Cognitive inertia
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cognitive_inertia
date_saved: 2026-05-05T09:57:22.921691+00:00
instance: kb-cron
parent: cognitive-inertia-20260505-0
summary:
=== Clinical diagnostics === In nosological literature relating to the symptom or disorder of apathy, clinicians have used cognitive inertia as one of the three main criteria for diagnosis. The description of cognitive inertia differs from its use in cognitive and industrial psychology in that lack of motivation plays a key role. As a clinical diagnostic criterion, Thant and Yager described it as "impaired abilities to elaborate and sustain goals and plans of actions, to shift mental sets, and to use working memory". This definition of apathy is frequently applied to onset of apathy due to neurodegenerative disorders such as Alzheimer's and Parkinson's disease but has also been applied to individuals who have gone through extreme trauma or abuse. == Neural anatomy and correlates == === Cortical === Cognitive inertia has been linked to decreased use of executive function, primarily in the prefrontal cortex, which aids in the flexibility of cognitive processes when switching tasks. Delayed response on the implicit associations task (IAT) and Stroop task have been related to an inability to combat cognitive inertia, as participants struggle to switch from one cognitive rule to the next to get the questions right. Before taking part in an electronic brainstorming


id: computational-heuristic-intelligence-20260505-0
file: data/en.wikipedia.org/wiki/Computational_heuristic_intelligence-0.md
category: reference
title: Computational heuristic intelligence
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Computational_heuristic_intelligence
date_saved: 2026-05-05T09:57:24.198634+00:00
instance: kb-cron
parent: computational-heuristic-intelligence-20260505-0
summary:
Computational heuristic intelligence (CHI) refers to specialized programming techniques in computational intelligence (also called artificial intelligence, or AI). These techniques have the express goal of avoiding complexity issues, also called NP-hard problems, by using human-like techniques. They are best summarized as the use of exemplar-based methods (heuristics), rather than rule-based methods (algorithms). Hence the term is distinct from the more conventional computational algorithmic intelligence, or symbolic AI. An example of a CHI technique is the encoding specificity principle of Tulving and Thompson. In general, CHI principles are problem solving techniques used by people, rather than programmed into machines. It is by drawing attention to this key distinction that the use of this term is justified in a field already replete with confusing neologisms. Note that the legal systems of all modern human societies employ both heuristics (generalisations of cases) from individual trial records as well as legislated statutes (rules) as regulatory guides. Another recent approach to the avoidance of complexity issues is to employ feedback control rather than feedforward modeling as a problem-solving paradigm. This approach has been called computational cybernetics, because (a) the term 'computational' is associated with conventional computer programming techniques which represent a strategic, compiled, or feedforward


id: consistent-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Consistent_heuristic-0.md
category: reference
title: Consistent heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Consistent_heuristic
date_saved: 2026-05-05T09:57:25.369916+00:00
instance: kb-cron
parent: consistent-heuristic-20260505-0
summary:
In the study of path-finding problems in artificial intelligence, a heuristic function is said to be consistent, or monotone, if its estimate is always less than or equal to the estimated distance from any neighbouring vertex to the goal, plus the cost of reaching that neighbour. Formally, for every node N and each successor P of N, the estimated cost of reaching the goal from N is no greater than the step cost of getting to P plus the estimated cost of reaching the goal from P. That is: h ( N ) ≤ c ( N , P ) + h ( P ) {\displaystyle h(N)\leq c(N,P)+h(P)} and h ( G ) = 0. {\displaystyle h(G)=0.\,} where h is the consistent heuristic function N is any node in the graph P is any descendant of N G is any goal node c(N,P) is the cost of reaching node P from N Informally, every node i will give an estimate that, accounting for the cost to reach the next node, is always lesser than or equal to the estimate at node i+1. A consistent heuristic is also admissible, i.e. it never overestimates the cost of reaching the goal (the converse,


id: consistent-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Consistent_heuristic-1.md
category: reference
title: Consistent heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Consistent_heuristic
date_saved: 2026-05-05T09:57:25.369916+00:00
instance: kb-cron
parent: consistent-heuristic-20260505-0
summary:
hence f ( P ) ≥ f ( N ) {\displaystyle f(P)\geq f(N)} . In the A* search algorithm, using a consistent heuristic means that once a node is expanded, the cost by which it was reached is the lowest possible, under the same conditions that Dijkstra's algorithm requires in solving the shortest path problem (no negative cost edges). In fact, if the search graph is given cost c ′ ( N , P ) = c ( N , P ) + h ( P ) − h ( N ) {\displaystyle c'(N,P)=c(N,P)+h(P)-h(N)} for a consistent h {\displaystyle h} , then A* is equivalent to best-first search on that graph using Dijkstra's algorithm. With a non-decreasing f ( N ) {\displaystyle f(N)} under consistent heuristics, one can show that A* achieves optimality with cycle-checking, that is, when A* expands a node n {\displaystyle n} , the optimal path to n {\displaystyle n} has already been found. Suppose for the sake of contradiction that when A* expands n {\displaystyle n} , the optimal path has not been found. Then, by the graph separation property, there must exist another node n ′ {\displaystyle n'} on the optimal path to n {\displaystyle


id: constructive-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Constructive_heuristic-0.md
category: reference
title: Constructive heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Constructive_heuristic
date_saved: 2026-05-05T09:57:26.519422+00:00
instance: kb-cron
parent: constructive-heuristic-20260505-0
summary:
A constructive heuristic is a type of heuristic method which starts with an empty solution and repeatedly extends the current solution until a complete solution is obtained. It differs from local search heuristics which start with a complete solution and then try to improve the current solution further via local moves. Examples of some famous problems that are solved using constructive heuristics are the flow shop scheduling, the vehicle routing problem and the open shop problem. == See also == Evolutionary algorithms Genetic algorithms Local search (optimization) Metaheuristics == References ==


id: contagion-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Contagion_heuristic-0.md
category: reference
title: Contagion heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Contagion_heuristic
date_saved: 2026-05-05T09:57:27.704654+00:00
instance: kb-cron
parent: contagion-heuristic-20260505-0
summary:
The contagion heuristic is a psychological heuristic which follows the law of contagion and the law of similarity, leading people to avoid contact with people or objects viewed as "contaminated" by previous contact with someone or something viewed as bad—or, less often, to seek contact with objects that have been in contact with people or things considered good. For example, people tend to view food that has touched the ground as contaminated by the ground, and therefore unfit to eat, or view a person who has touched a diseased person as likely to carry the disease (regardless of the actual contagiousness of the disease). The contagion heuristic can include "magical thinking", in which well-educated adults will think that touching an object transfers their qualities ("essence") to it: for example, a sweater worn by Adolf Hitler is thought to bear his negative essence and to be capable of transmitting it to another wearer. The perception of essence-transfer extends to rituals to purify items viewed as spiritually contaminated, such as having Mother Teresa wear Hitler's sweater to counteract his essence. == Types == The contagion heuristic can be separated into three categories: === 1. Positive or negative === Contagion can be negative


id: contagion-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Contagion_heuristic-1.md
category: reference
title: Contagion heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Contagion_heuristic
date_saved: 2026-05-05T09:57:27.704654+00:00
instance: kb-cron
parent: contagion-heuristic-20260505-0
summary:
A rejection of potentially offensive food: People are unlikely to touch foods that elicit disgust in attempts to protect our health (e.g. disgust towards uncooked chicken as it is seen as contaminated with potential harmful microorganisms like salmonella). Illness transfer between humans: Avoid touching a 'contaminated' ill person due to fear of getting ill. Support Relationships: Positive contagion encourages highly intimate acts with people perceived as positively contaminated such as family and lovers. (sexual intimacy which would otherwise elicit disgust without love and lust) Hence, the contagion heuristic seems to be a pre-adaptation, that is it evolved to be beneficial to health and relationships, supporting the survival of our species, but now no longer serves a person in the current environment. == Critiques == Positive contagion is relatively weak and might just be an over-extension of the negative contagion principle. This is most likely due to the negative bias: that is, when given two cases, one of negative and one of positive of equal force, the negative case will have a greater impact. As an old Russian phrase states, "A spoonful of tar can spoil a barrel of honey, but a spoonful of honey does nothing for a barrel of


id: content-sniffing-20260505-0
file: data/en.wikipedia.org/wiki/Content_sniffing-0.md
category: reference
title: Content sniffing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Content_sniffing
date_saved: 2026-05-05T09:57:28.890773+00:00
instance: kb-cron
parent: content-sniffing-20260505-0
summary:
Content sniffing, also known as media type sniffing or MIME sniffing, is the practice of inspecting the content of a byte stream to attempt to deduce the file format of the data within it. Content sniffing is generally used to compensate for a lack of accurate metadata that would otherwise be required to enable the file to be interpreted correctly. Content sniffing techniques tend to use a mixture of techniques that rely on the redundancy found in most file formats: looking for file signatures and magic numbers, and heuristics including searching for well-known representative substrings, the use of byte frequency and n-gram tables, and Bayesian inference. Multipurpose Internet Mail Extensions (MIME) sniffing was, and still is, used by some web browsers, including notably Microsoft's Internet Explorer, in an attempt to help web sites which do not correctly signal the MIME type of web content display. However, doing this opens up a serious security vulnerability, in which, by confusing the MIME sniffing algorithm, the browser can be manipulated into interpreting data in a way that allows an attacker to carry out operations that are not expected by either the site operator or user, such as cross-site scripting. Moreover, by making sites


id: cross-entropy-method-20260505-0
file: data/en.wikipedia.org/wiki/Cross-entropy_method-0.md
category: reference
title: Cross-entropy method
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cross-entropy_method
date_saved: 2026-05-05T09:57:30.044973+00:00
instance: kb-cron
parent: cross-entropy-method-20260505-0
summary:
The cross-entropy (CE) method is a Monte Carlo method for importance sampling and optimization. It is applicable to both combinatorial and continuous problems, with either a static or noisy objective. The method approximates the optimal importance sampling estimator by repeating two phases: Draw a sample from a probability distribution. Minimize the cross-entropy between this distribution and a target distribution to produce a better sample in the next iteration. Reuven Rubinstein developed the method in the context of rare-event simulation, where tiny probabilities must be estimated, for example in network reliability analysis, queueing models, or performance analysis of telecommunication systems. The method has also been applied to the traveling salesman, quadratic assignment, DNA sequence alignment, max-cut and buffer allocation problems. == Estimation via importance sampling == Consider the general problem of estimating the quantity ℓ = E u [ H ( X ) ] = ∫ H ( x ) f ( x ; u ) d x {\displaystyle \ell =\mathbb {E} _{\mathbf {u} }[H(\mathbf {X} )]=\int H(\mathbf {x} )\,f(\mathbf {x} ;\mathbf {u} )\,{\textrm {d}}\mathbf {x} } , where H {\displaystyle H} is some performance function and f ( x ; u ) {\displaystyle f(\mathbf {x} ;\mathbf {u} )} is a


id: debiasing-20260505-0
file: data/en.wikipedia.org/wiki/Debiasing-0.md
category: reference
title: Debiasing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Debiasing
date_saved: 2026-05-05T09:57:31.215378+00:00
instance: kb-cron
parent: debiasing-20260505-0
summary:
Debiasing is the reduction of bias, particularly with respect to judgment and decision making. Biased judgment and decision making is that which systematically deviates from the prescriptions of objective standards such as facts, logic, and rational behavior or prescriptive norms. Biased judgment and decision making exists in consequential domains such as medicine, law, policy, and business, as well as in everyday life. Investors, for example, tend to exhibit the disposition effect by holding onto falling stocks too long and selling rising stocks too quickly. Employers exhibit considerable discrimination in hiring and employment practices, and some parents continue to believe that vaccinations cause autism despite knowing that this link is based on falsified evidence. At an individual level, people who exhibit less decision bias have more intact social environments, reduced risk of alcohol and drug use, lower childhood delinquency rates, and superior planning and problem solving abilities. Debiasing can occur within the decision maker. For example, a person may learn or adopt better strategies by which to make judgments and decisions. Debiasing can also occur as a result of changes in external factors, such as changing the incentives relevant to a decision or the manner in which the decision is made.


id: debiasing-20260505-1
file: data/en.wikipedia.org/wiki/Debiasing-1.md
category: reference
title: Debiasing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Debiasing
date_saved: 2026-05-05T09:57:31.215378+00:00
instance: kb-cron
parent: debiasing-20260505-0
summary:
=== Incentives === Paying people for optimal behavior through bonuses or by providing discounts (e.g., to exercise, to take their medication, to trade in fuel inefficient vehicles such as the "cash for clunkers" program). Taxing people for suboptimal behavior (e.g., drinking soda, smoking tobacco, and weed). === Nudges === Using default effect to nudge people towards decisions optimal for the decision maker or society. Commitment devices that makes it more costly to make suboptimal decisions (e.g., Schwartz et al., 2014). Reframing choice options in ways that make important attributes salient. Labeling hamburger meat 25% fat, for example, makes people more sensitive to fat content than labeling it 75% lean. Presenting information in formats that make critical information easier to evaluate, such as displaying nutritional value using a "traffic light" system. === Training === Providing people with personalized feedback regarding the direction and degree to which they exhibit bias. Teaching a "consider-the-alternative" strategy, such as considering a plausible alternative reason for an event than cause one suspects. Teaching people statistical reasoning and normative rules of which they are unaware. Encouraging people to take the perspective of a person who will experience the consequences of their decision can reduce bias. Participants who


id: distributional-relational-database-20260505-0
file: data/en.wikipedia.org/wiki/Distributional–relational_database-0.md
category: reference
title: Distributional–relational database
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Distributional–relational_database
date_saved: 2026-05-05T09:57:32.392660+00:00
instance: kb-cron
parent: distributional-relational-database-20260505-0
summary:
A distributional–relational database, or word-vector database, is a database management system (DBMS) that uses distributional word-vector representations to enrich the semantics of structured data. As distributional word-vectors can be built automatically from large-scale corpora, this enrichment supports the construction of databases which can embed large-scale commonsense background knowledge into their operations. Distributional-Relational models can be applied to the construction of schema-agnostic databases (databases in which users can query the data without being aware of its schema), semantic search, schema-integration and inductive and abductive reasoning as well as different applications in which a semantically flexible knowledge representation model is needed. The main advantage of distributional–relational models over purely logical or semantic web models is the fact that the core semantic associations can be automatically captured from corpora, in contrast to the definition of manually curated ontologies and rule knowledge bases. == Distributional–relational models == Distributional–relational models were first formalized as a mechanism to cope with the vocabulary/semantic gap between users and the schema behind the data. In this scenario, distributional semantic relatedness measures, combined with semantic pivoting heuristics can support the approximation between user queries (expressed in their own vocabulary), and data (expressed in the vocabulary of the designer). In this


id: duck-test-20260505-0
file: data/en.wikipedia.org/wiki/Duck_test-0.md
category: reference
title: Duck test
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Duck_test
date_saved: 2026-05-05T09:57:33.627172+00:00
instance: kb-cron
parent: duck-test-20260505-0
summary:
The duck test is a frequently cited colloquial example of abductive reasoning. Its usual expression is: If it looks like a duck, swims like a duck, and quacks like a duck, then it probably is a duck. The test implies that a person can identify an unknown subject by observing that subject's habitual characteristics. It is sometimes used to counter abstract arguments that something might not be what it appears to be. == Notable uses == Indiana poet James Whitcomb Riley (1849–1916) may have coined the phrase when he wrote: When I see a bird that walks like a duck and swims like a duck and quacks like a duck, I call that bird a duck. A common variation of the wording of the phrase may have originated much later with Emil Mazey, secretary-treasurer of the United Auto Workers, at a labor meeting in 1946 accusing a person of being a communist: I can't prove you are a Communist. But when I see a bird that quacks like a duck, walks like a duck, has feathers and webbed feet and associates with ducks—I'm certainly going to assume that he is a duck. The term was later popularized in the United


id: effort-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Effort_heuristic-0.md
category: reference
title: Effort heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Effort_heuristic
date_saved: 2026-05-05T09:57:34.737352+00:00
instance: kb-cron
parent: effort-heuristic-20260505-0
summary:
The effort heuristic is a mental rule of thumb in which the quality or worth of an object is determined from the perceived amount of effort that went into producing that object. In brief, the effort heuristic follows a tendency to judge objects that took a longer time to produce to be of higher value. The more effort invested in an object, the better it is deemed to be. This is especially true in situations where value is difficult to assess or the evaluator lacks expertise in the appraisement of an item. People use whatever information is available to them and effort is thought to generally be a reliable indicator of quality. An example of this would be the comparison of $100 earned, and $100 found. If someone finds $100 they are more inclined to go spend it on a whim, but if that $100 is part of a hard-earned paycheck, they are less likely to squander it away. Another way that effort heuristic can be considered is the amount of effort a person will put into an action depending on the goal. If the goal is of little importance, the amount of effort a person is willing to put


id: effort-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Effort_heuristic-1.md
category: reference
title: Effort heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Effort_heuristic
date_saved: 2026-05-05T09:57:34.737352+00:00
instance: kb-cron
parent: effort-heuristic-20260505-0
summary:
== Explanations == Human behavior, like that of most other animals, is often driven by rewards and directed by the energetic cost of an action. It takes effort to attain rewards, and people accordingly weigh the value of rewards against the amount of effort that is required to attain them. At an early age, children learn that good performance due to high effort is valued by adults and that teachers are most likely to reward those who work hard. With experience, they internalize effort as a valuable commodity. == Alternative theories == Research directly examining and testing the effort heuristic is scarce, however there are other research areas that incorporated this construct and, in some way, manipulated its effects. However, a key distinction between the study done by Kruger et al. and other research on the role of effort on judgment is that the former focused on other-generated effort rather than self-generated effort. === Cognitive dissonance === ==== Effort justification ==== Over half a century ago, social psychologist Leon Festinger developed the theory of cognitive dissonance. It asserts that inconsistencies among a person's beliefs, attitudes, or opinions produce psychological discomfort, leading people to rationalize their behavior or change their attitudes.


id: eurisko-20260505-0
file: data/en.wikipedia.org/wiki/Eurisko-0.md
category: reference
title: Eurisko
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eurisko
date_saved: 2026-05-05T09:57:35.937717+00:00
instance: kb-cron
parent: eurisko-20260505-0
summary:
Eurisko (Gr., I discover) is a discovery system written by Douglas Lenat in RLL-1, a representation language itself written in the Lisp programming language. A sequel to Automated Mathematician, it consists of heuristics, i.e. rules of thumb, including heuristics describing how to use and change its own heuristics. Lenat was frustrated by Automated Mathematician's constraint to a single domain and so developed Eurisko; his frustration with the effort of encoding domain knowledge for Eurisko led to Lenat's subsequent development of Cyc. Lenat envisioned ultimately coupling the Cyc knowledge base with the Eurisko discovery engine. == History == Development commenced at Carnegie Mellon in 1976 and continued at Stanford University in 1978 when Lenat returned to teach. "For the first five years, nothing good came out of it", Lenat said. But when the implementation was changed to a frame language based representation he called RLL (Representation Language Language), heuristic creation and modification became much simpler. Eurisko was then applied to a number of domains with surprising success, including VLSI chip design. Previously, Lenat had worked at the automatic-programming research group at the Stanford Artificial Intelligence Laboratory, and was coauthor of a report in 1974 on "Program-Understanding Systems". Inspired by work on


id: evaluation-function-20260505-0
file: data/en.wikipedia.org/wiki/Evaluation_function-0.md
category: reference
title: Evaluation function
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Evaluation_function
date_saved: 2026-05-05T09:57:37.091312+00:00
instance: kb-cron
parent: evaluation-function-20260505-0
summary:
An evaluation function, also known as a heuristic evaluation function or static evaluation function, is a function used by game-playing computer programs to estimate the value or goodness of a position (usually at a leaf or terminal node) in a game tree. Most of the time, the value is either a real number or a quantized integer, often in nths of the value of a playing piece such as a stone in go or a pawn in chess, where n may be tenths, hundredths or other convenient fraction, but sometimes, the value is an array of three values in the unit interval, representing the win, draw, and loss percentages of the position. There do not exist analytical or theoretical models for evaluation functions for unsolved games, nor are such functions entirely ad-hoc. The composition of evaluation functions is determined empirically by inserting a candidate function into an automaton and evaluating its subsequent performance. A significant body of evidence now exists for several games like chess, shogi and go as to the general composition of evaluation functions for them. Games in which game playing computer programs employ evaluation functions include chess, go, shogi (Japanese chess), othello, hex, backgammon, and checkers. In


id: evaluation-function-20260505-1
file: data/en.wikipedia.org/wiki/Evaluation_function-1.md
category: reference
title: Evaluation function
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Evaluation_function
date_saved: 2026-05-05T09:57:37.091312+00:00
instance: kb-cron
parent: evaluation-function-20260505-0
summary:
c1 * material + c2 * mobility + c3 * king safety + c4 * center control + c5 * pawn structure + c6 * king tropism + ... Each of the terms is a weight multiplied by a difference factor: the value of white's material or positional terms minus black's. The material term is obtained by assigning a value in pawn-units to each of the pieces. Mobility is the number of legal moves available to a player, or alternately the sum of the number of spaces attacked or defended by each piece, including spaces occupied by friendly or opposing pieces. Effective mobility, or the number of "safe" spaces a piece may move to, may also be taken into account. King safety is a set of bonuses and penalties assessed for the location of the king and the configuration of pawns and pieces adjacent to or in front of the king, and opposing pieces bearing on spaces around the king. Center control is derived from how many pawns and pieces occupy or bear on the four center spaces and sometimes the 12 spaces of the extended center. Pawn structure is a set of penalties and bonuses for various strengths and


id: extremal-optimization-20260505-0
file: data/en.wikipedia.org/wiki/Extremal_optimization-0.md
category: reference
title: Extremal optimization
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Extremal_optimization
date_saved: 2026-05-05T09:57:38.266316+00:00
instance: kb-cron
parent: extremal-optimization-20260505-0
summary:
Extremal optimization (EO) is an optimization heuristic inspired by the Bak–Sneppen model of self-organized criticality from the field of statistical physics. This heuristic was designed initially to address combinatorial optimization problems such as the travelling salesman problem and spin glasses, although the technique has been demonstrated to function in optimization domains. == Relation to self-organized criticality == Self-organized criticality (SOC) is a statistical physics concept to describe a class of dynamical systems that have a critical point as an attractor. Specifically, these are non-equilibrium systems that evolve through avalanches of change and dissipations that reach up to the highest scales of the system. SOC is said to govern the dynamics behind some natural systems that have these burst-like phenomena including landscape formation, earthquakes, evolution, and the granular dynamics of rice and sand piles. Of special interest here is the Bak–Sneppen model of SOC, which is able to describe evolution via punctuated equilibrium (extinction events) – thus modelling evolution as a self-organised critical process. == Relation to computational complexity == Another piece in the puzzle is work on computational complexity, specifically that critical points have been shown to exist in NP-complete problems, where near-optimum solutions are widely dispersed and separated by


id: extremal-optimization-20260505-1
file: data/en.wikipedia.org/wiki/Extremal_optimization-1.md
category: reference
title: Extremal optimization
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Extremal_optimization
date_saved: 2026-05-05T09:57:38.266316+00:00
instance: kb-cron
parent: extremal-optimization-20260505-0
summary:
== References == Bak, Per; Tang, Chao; Wiesenfeld, Kurt (1987-07-27). "Self-organized criticality: An explanation of the 1/fnoise". Physical Review Letters. 59 (4). American Physical Society (APS): 381–384. Bibcode:1987PhRvL..59..381B. doi:10.1103/physrevlett.59.381. ISSN 0031-9007. PMID 10035754. S2CID 7674321. Bak, Per; Sneppen, Kim (1993-12-13). "Punctuated equilibrium and criticality in a simple model of evolution". Physical Review Letters. 71 (24). American Physical Society (APS): 4083–4086. Bibcode:1993PhRvL..71.4083B. doi:10.1103/physrevlett.71.4083. ISSN 0031-9007. PMID 10055149. P Cheeseman, B Kanefsky, WM Taylor, "Where the really hard problems are", Proceedings of the 12th IJCAI, (1991) G Istrate, "Computational complexity and phase transitions", Proceedings. 15th Annual IEEE Conference on Computational Complexity, 104–115 (2000) Stefan Boettcher, Allon G. Percus, "Extremal Optimization: Methods derived from Co-Evolution", Proceedings of the Genetic and Evolutionary Computation Conference (1999) Boettcher, Stefan (1999-01-01). "Extremal optimization of graph partitioning at the percolation threshold". Journal of Physics A: Mathematical and General. 32 (28). IOP Publishing: 5201–5211. arXiv:cond-mat/9901353. Bibcode:1999JPhA...32.5201B. doi:10.1088/0305-4470/32/28/302. ISSN 0305-4470. S2CID 7925735. Boettcher, Stefan; Percus, Allon (2000), "Nature's way of optimizing", Artificial Intelligence, 119 (1–2): 275–286, arXiv:cond-mat/9901351, doi:10.1016/S0004-3702(00)00007-2, S2CID 7128022 Boettcher, S. (2000). "Extremal optimization: heuristics via coevolutionary avalanches". Computing in Science & Engineering. 2 (6). Institute of Electrical and Electronics Engineers (IEEE): 75–82. arXiv:cond-mat/0006374. Bibcode:2000CSE.....2f..75B. doi:10.1109/5992.881710. ISSN 1521-9615. S2CID


id: familiarity-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Familiarity_heuristic-0.md
category: reference
title: Familiarity heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Familiarity_heuristic
date_saved: 2026-05-05T09:57:39.450812+00:00
instance: kb-cron
parent: familiarity-heuristic-20260505-0
summary:
In psychology, a heuristic is an easy-to-compute procedure or rule of thumb that people use when forming beliefs, judgments or decisions. The familiarity heuristic was developed based on the discovery of the availability heuristic by psychologists Amos Tversky and Daniel Kahneman; it happens when the familiar is favored over novel places, people, or things. The familiarity heuristic can be applied to various situations that individuals experience in day-to-day life. When these situations appear similar to previous situations, especially if the individuals are experiencing a high cognitive load, they may regress to the state of mind in which they have felt or behaved before. This heuristic is useful in most situations and can be applied to many fields of knowledge; however, there are both positives and negatives to this heuristic as well. == Origin == === Availability heuristic === The familiarity heuristic stems from the availability heuristic, which was studied by Tversky and Kahneman. The availability heuristic suggests that the likelihood of events is estimated based on how many examples of such events come to mind. Thus the familiarity heuristic shows how "bias of availability is related to the ease of recall." Tversky and Kahneman created an experiment in order to


id: fast-and-frugal-trees-20260505-0
file: data/en.wikipedia.org/wiki/Fast-and-frugal_trees-0.md
category: reference
title: Fast-and-frugal trees
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fast-and-frugal_trees
date_saved: 2026-05-05T09:57:40.653304+00:00
instance: kb-cron
parent: fast-and-frugal-trees-20260505-0
summary:
Fast-and-frugal tree or matching heuristic (in the study of decision-making) is a simple graphical structure that categorizes objects by asking one question at a time. These decision trees are used in a range of fields: psychology, artificial intelligence, and management science. Unlike other decision or classification trees, such as Leo Breiman's CART, fast-and-frugal trees are intentionally simple, both in their construction as well as their execution, and operate speedily with little information. For this reason, fast-and-frugal-trees are potentially attractive when designing resource-constrained tasks. Laura Martignon, Vitouch, Takezawa and Forster first introduced both the concept and the term in 2003; similar heuristics for other tasks had been used before, building on the formal models created by Gerd Gigerenzer and Herbert A. Simon. In categorization tasks with two options and m cues—also known as features or attributes—available for making such a decision, an FFT is defined as follows: A fast-and-frugal tree is a classification or a decision tree that has m+1 exits, with one exit for each of the first m −1 cues and two exits for the last cue. Mathematically, fast-and-frugal trees can be viewed as lexicographic heuristics or as linear classification models with non-compensatory weights and a threshold.[MKW] Their formal


id: fast-and-frugal-trees-20260505-1
file: data/en.wikipedia.org/wiki/Fast-and-frugal_trees-1.md
category: reference
title: Fast-and-frugal trees
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fast-and-frugal_trees
date_saved: 2026-05-05T09:57:40.653304+00:00
instance: kb-cron
parent: fast-and-frugal-trees-20260505-0
summary:
=== Signal detection analysis === Fast-and-frugal trees are used to perform binary classifications or decisions. In psychology, medicine, and other fields, signal detection theory (or detection theory) has been the classic theory under which such tasks are analyzed. The theory assumes that there are two categories of events or people (e.g., people with and without heart problems), of which the category more relevant to us is referred as "signal" while the other is referred to as "noise". The two differ in their distribution on an observation scale that we may call "evidence", with the signal distribution having a higher mean. One can make two possible classifications, namely "signal" or "noise", upon gathering the evidence. This leads to four possible outcomes: hit (classify as "signal" when it is indeed a signal), correct rejection (classify as "noise" when it is indeed a noise), miss (classify as "noise" when it is actually a signal), and false alarm (classify as "signal" when it is actually a noise). To maximize overall accuracy or the expected value of a classification, the theory posits that we need to carefully select the classification criterion on the evidence scale, above which we make a "signal" decision and below which


id: fly-algorithm-20260505-0
file: data/en.wikipedia.org/wiki/Fly_algorithm-0.md
category: reference
title: Fly algorithm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fly_algorithm
date_saved: 2026-05-05T09:57:41.802183+00:00
instance: kb-cron
parent: fly-algorithm-20260505-0
summary:
The Fly Algorithm is an approach in 3D reconstruction that utilizes clusters of points ("flies") corresponding to different nearby objects via genetic algorithms and stereovision principles. The resulting reconstruction is partial, but can be used to recognize obstacles in robot navigation and other applications. This technique has a high computational load due to numerous inputs and parameters, making performance optimization difficult. == History == The Fly Algorithm is a type of cooperative coevolution based on the Parisian approach. The Fly Algorithm has first been developed in 1999 in the scope of the application of Evolutionary algorithms to computer stereo vision. Unlike the classical image-based approach to stereovision, which extracts image primitives then matches them in order to obtain 3-D information, the Fly Algorithm is based on the direct exploration of the 3-D space of the scene. A fly is defined as a 3-D point described by its coordinates (x, y, z). Once a random population of flies has been created in a search space corresponding to the field of view of the cameras, its evolution (based on the Evolutionary Strategy paradigm) used a fitness function that evaluates how likely the fly is lying on the visible surface of an object,


id: fly-algorithm-20260505-1
file: data/en.wikipedia.org/wiki/Fly_algorithm-1.md
category: reference
title: Fly algorithm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fly_algorithm
date_saved: 2026-05-05T09:57:41.802183+00:00
instance: kb-cron
parent: fly-algorithm-20260505-0
summary:
=== Parisian approach vs cooperative coevolution === Cooperative coevolution is a broad class of evolutionary algorithms where a complex problem is solved by decomposing it into subcomponents that are solved independently. The Parisian approach shares many similarities with the cooperative coevolutionary algorithm. The Parisian approach makes use of a single-population whereas multi-species may be used in cooperative coevolutionary algorithm. Similar internal evolutionary engines are considered in classical evolutionary algorithm, cooperative coevolutionary algorithm and Parisian evolution. The difference between cooperative coevolutionary algorithm and Parisian evolution resides in the population's semantics. Cooperative coevolutionary algorithm divides a big problem into sub-problems (groups of individuals) and solves them separately toward the big problem. There is no interaction/breeding between individuals of the different sub-populations, only with individuals of the same sub-population. However, Parisian evolutionary algorithms solve a whole problem as a big component. All population's individuals cooperate together to drive the whole population toward attractive areas of the search space. === Fly Algorithm vs particle swarm optimisation === Cooperative coevolution and particle swarm optimisation (PSO) share many similarities. PSO is inspired by the social behaviour of bird flocking or fish schooling. It was initially introduced as a tool for realistic animation in computer graphics. It


id: fly-algorithm-20260505-2
file: data/en.wikipedia.org/wiki/Fly_algorithm-2.md
category: reference
title: Fly algorithm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fly_algorithm
date_saved: 2026-05-05T09:57:41.802183+00:00
instance: kb-cron
parent: fly-algorithm-20260505-0
summary:
algorithm fly-algorithm is input: number of flies (N), input projection data (preference) output: the fly population (F), the projections estimated from F (pestimated) the 3-D volume corresponding to the voxelisation of F (VF) postcondition: the difference between pestimated and preference is minimal. START 1. // Initialisation 2. // Set the position of the N flies, i.e. create initial guess 3. for each fly i in fly population F do 4. F(i)x ← random(0, 1) 5. F(i)y ← random(0, 1) 6. F(i)z ← random(0, 1) 7. Add F(i)'s projection in pestimated 8. 9. // Compute the population's performance (i.e. the global fitness) 10. Gfitness(F) ← Errormetrics(preference, pestimated) 11. 12. fkill ← Select a random fly of F 13. 14. Remove fkill's contribution from pestimated 15. 16. // Compute the population's performance without fkill 17. Gfitness(F-{fkill}) ← Errormetrics(preference, pestimated) 18. 19. // Compare the performances, i.e. compute the fly's local fitness 20. Lfitness(fkill) ← Gfitness(F-{fkill}) - Gfitness(F) 21. 22. If the local fitness is greater than 0, // Thresholded-selection of a bad fly that can be killed 23. then go to Step 26. // fkill is a good fly (the population's performance is better when fkill is included): we should not kill


id: forensic-science-20260505-0
file: data/en.wikipedia.org/wiki/Forensic_science-0.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
Forensic science, often known as with criminalistics, is the application of science principles and methods to support decision-making related to rules or law, generally criminal and civil law. During criminal investigation in particular, it is governed by the legal standards of admissible evidence and criminal procedure. It is a broad field utilizing numerous practices such as the analysis of DNA, fingerprints, bloodstain patterns, firearms, ballistics, toxicology, microscopy, and fire debris analysis. Modern forensic analysis is also conducted on cybersecurity related incidents where major breach has occurred leading to substantial financial loss. Forensic scientists collect, preserve, and analyze evidence during the course of an investigation. While some forensic scientists travel to the scene of the crime to collect the evidence themselves, others occupy a laboratory role, performing analysis on objects brought to them by other individuals. Others are involved in analysis of financial, banking, or other numerical data for use in financial crime investigation, and can be employed as consultants from private firms, academia, or as government employees. In addition to their laboratory role, forensic scientists testify as expert witnesses in both criminal and civil cases and can work for either the prosecution or the defense. While any field could technically


id: forensic-science-20260505-1
file: data/en.wikipedia.org/wiki/Forensic_science-1.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
== Education and training == Initial glance, forensic intelligence may appear as a nascent facet of forensic science facilitated by advancements in information technologies such as computers, databases, and data-flow management software. However, a more profound examination reveals that forensic intelligence represents a genuine and emerging inclination among forensic practitioners to actively participate in investigative and policing strategies. In doing so, it elucidates existing practices within scientific literature, advocating for a paradigm shift from the prevailing conception of forensic science as a conglomerate of disciplines merely aiding the criminal justice system. Instead, it urges a perspective that views forensic science as a discipline studying the informative potential of traces—remnants of criminal activity. Embracing this transformative shift poses a significant challenge for education, necessitating a shift in learners' mindset to accept concepts and methodologies in forensic intelligence. Recent calls advocating for the integration of forensic scientists into the criminal justice system, as well as policing and intelligence missions, underscore the necessity for the establishment of educational and training initiatives in the field of forensic intelligence. This article contends that a discernible gap exists between the perceived and actual comprehension of forensic intelligence among law enforcement and forensic science managers, positing that


id: forensic-science-20260505-2
file: data/en.wikipedia.org/wiki/Forensic_science-2.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
James Marsh was the first to apply this new science to the art of forensics. He was called by the prosecution in a murder trial to give evidence as a chemist in 1832. The defendant, John Bodle, was accused of poisoning his grandfather with arsenic-laced coffee. Marsh performed the standard test by mixing a suspected sample with hydrogen sulfide and hydrochloric acid. While he was able to detect arsenic as yellow arsenic trisulfide, when it was shown to the jury it had deteriorated, allowing the suspect to be acquitted due to reasonable doubt. Annoyed by that, Marsh developed a much better test. He combined a sample containing arsenic with sulfuric acid and arsenic-free zinc, resulting in arsine gas. The gas was ignited, and it decomposed to pure metallic arsenic, which, when passed to a cold surface, would appear as a silvery-black deposit. So sensitive was the test, known formally as the Marsh test, that it could detect as little as one-fiftieth of a milligram of arsenic. He first described this test in The Edinburgh Philosophical Journal in 1836. === Ballistics and firearms === Ballistics is "the science of the motion of projectiles in flight". In forensic science, analysts examine the


id: forensic-science-20260505-3
file: data/en.wikipedia.org/wiki/Forensic_science-3.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
=== Uhlenhuth test === The Uhlenhuth test, or the antigen–antibody precipitin test for species, was invented by Paul Uhlenhuth in 1901 and could distinguish human blood from animal blood, based on the discovery that the blood of different species had one or more characteristic proteins. The test represented a major breakthrough and came to have tremendous importance in forensic science. The test was further refined for forensic use by the Swiss chemist Maurice Müller in the year 1960s. === DNA === Forensic DNA analysis was first used in 1984. It was developed by Sir Alec Jeffreys, who realized that variation in the genetic sequence could be used to identify individuals and to tell individuals apart from one another. The first application of DNA profiles was used by Jeffreys in a double murder mystery in the small English town of Narborough, Leicestershire, in 1985. A 15-year-old school girl by the name of Lynda Mann was raped and murdered in Carlton Hayes psychiatric hospital. The police did not find a suspect but were able to obtain a semen sample. In 1986, Dawn Ashworth, 15 years old, was also raped and strangled in the nearby village of Enderby. Forensic evidence showed that both


id: forensic-science-20260505-4
file: data/en.wikipedia.org/wiki/Forensic_science-4.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
Handbook for Coroners, police officials, military policemen was written by the Austrian criminal jurist Hans Gross in 1893, and is generally acknowledged as the birth of the field of criminalistics. The work combined in one system fields of knowledge that had not been previously integrated, such as psychology and physical science, and which could be successfully used against crime. Gross adapted some fields to the needs of criminal investigation, such as crime scene photography. He went on to found the Institute of Criminalistics in 1912, as part of the University of Graz' Law School. This Institute was followed by many similar institutes all over the world. In 1909, Archibald Reiss founded the Institut de police scientifique of the University of Lausanne (UNIL), the first school of forensic science in the world. Dr. Edmond Locard, became known as the "Sherlock Holmes of France". He formulated the basic principle of forensic science: "Every contact leaves a trace", which became known as Locard's exchange principle. In 1910, he founded what may have been the first criminal laboratory in the world, after persuading the Police Department of Lyon (France) to give him two attic rooms and two assistants. Symbolic of the newfound prestige of


id: forensic-science-20260505-5
file: data/en.wikipedia.org/wiki/Forensic_science-5.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
=== 21st century === In the past decade, documenting forensics scenes has become more efficient. Forensic scientists have started using laser scanners, drones and photogrammetry to obtain 3D point clouds of accidents or crime scenes. Reconstruction of an accident scene on a highway using drones involves data acquisition time of only 10–20 minutes and can be performed without shutting down traffic. The results are not just accurate, in centimeters, for measurement to be presented in court but also easy to digitally preserve in the long term. Now, in the 21st century, much of forensic science's future is up for discussion. The National Institute of Standards and Technology (NIST) has several forensic science-related programs: CSAFE, a NIST Center of Excellence in Forensic Science, the National Commission on Forensic Science (now concluded), and administration of the Organization of Scientific Area Committees for Forensic Science (OSAC). One of the more recent additions by NIST is a document called NISTIR-7941, titled "Forensic Science Laboratories: Handbook for Facility Planning, Design, Construction, and Relocation". The handbook provides a clear blueprint for approaching forensic science. The details even include what type of staff should be hired for certain positions. == Subdivisions == Art forensics concerns the art


id: forensic-science-20260505-6
file: data/en.wikipedia.org/wiki/Forensic_science-6.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
== Questionable techniques == Some forensic techniques, believed to be scientifically sound at the time they were used, have turned out later to have much less scientific merit or none. Some such techniques include: Comparative bullet-lead analysis was used by the FBI for over four decades, starting with the John F. Kennedy assassination in 1963. The theory was that each batch of ammunition possessed a chemical makeup so distinct that a bullet could be traced back to a particular batch or even a specific box. Internal studies and an outside study by the National Academy of Sciences found that the technique was unreliable due to improper interpretation, and the FBI abandoned the test in 2005. Forensic dentistry has come under fire: in at least three cases bite-mark evidence has been used to convict people of murder who were later freed by DNA evidence. A 1999 study by a member of the American Board of Forensic Odontology found a 63 percent rate of false identifications and is commonly referenced within online news stories and conspiracy websites. The study was based on an informal workshop during an ABFO meeting, which many members did not consider a valid scientific setting. The theory is


id: forensic-science-20260505-7
file: data/en.wikipedia.org/wiki/Forensic_science-7.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
== Controversies == Questions about certain areas of forensic science, such as fingerprint evidence and the assumptions behind these disciplines have been brought to light in some publications including the New York Post. The article stated that "No one has proved even the basic assumption: That everyone's fingerprint is unique." The article also stated that "Now such assumptions are being questioned—and with it may come a radical change in how forensic science is used by police departments and prosecutors." Law professor Jessica Gabel said on NOVA that forensic science "lacks the rigors, the standards, the quality controls and procedures that we find, usually, in science". The National Institute of Standards and Technology has reviewed the scientific foundations of bite-mark analysis used in forensic science. Bite mark analysis is a forensic science technique that analyzes the marks on the victim's skin compared to the suspects teeth. NIST reviewed the findings of the National Academies of Sciences, Engineering, and Medicine 2009 study. The National Academics of Sciences, Engineering, and Medicine conducted research to address the issues of reliability, accuracy, and reliability of bitemark analysis, where they concluded that there is a lack of sufficient scientific foundation to support the data. Yet the


id: forensic-science-20260505-8
file: data/en.wikipedia.org/wiki/Forensic_science-8.md
category: reference
title: Forensic science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Forensic_science
date_saved: 2026-05-05T09:57:43.032936+00:00
instance: kb-cron
parent: forensic-science-20260505-0
summary:
Association of Firearm and Tool Mark Examiners – International non-profit organization Canadian Identification Society Computer forensics – Branch of digital forensic science Crime science – Study of ways to prevent or reduce crime Diplomatics – Academic study of the protocols of documents (forensic paleography) Epigenetics in forensic science – Overview article Evidence packaging – Specialized packaging for physical evidence Forensic biology – Forensic application of the study of biology Forensic economics Forensic identification – Legal identification of specific objects and materials Forensic materials engineering – Branch of forensic engineering Forensic photography – Art of producing an accurate reproduction of a crime scene Forensic polymer engineering – Study of failure in polymeric products Forensic profiling – Study of trace evidence in criminal investigations Glove prints – Mark left on a surface by a worn glove History of forensic photography International Association for Identification Medical jurisprudence – Branch of science and medicine Marine forensics Outline of forensic science – Overview of and topical guide to forensic science Profiling (information science) – Creation and use of user profiles via data analysis Retrospective diagnosis – Practice of identifying an illness after the death of the patient Rapid Stain Identification Series (RSID) Scenes of crime


id: frecency-20260505-0
file: data/en.wikipedia.org/wiki/Frecency-0.md
category: reference
title: Frecency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Frecency
date_saved: 2026-05-05T09:57:44.201081+00:00
instance: kb-cron
parent: frecency-20260505-0
summary:
In computing, frecency is any heuristic that combines the frequency and recency into a single measure. == Heuristic == In its simplest form, the frequency and recency rating can be added to form a frecency rating. The ratings can be found by sorting items by most recent and most frequent respectively. A decayed calculation using logarithms can also be used. == Examples == Some web browsers use frecency to predict the likelihood of revisiting a given web page or reusing a given HTTP cache entry "Frecency is a score given to each unique URI in Places, encompassing bookmarks, history and tags. This score is determined by the amount of revisitation, the type of those visits, how recent they were, and whether the URI was bookmarked or tagged." Frecency can be computed from a list of use dates, either as pro-actively while a user browses the web or as needed. Some frecency measures can also be computed in a rolling manner without storing such a list. The ZFS filesystem uses this concept in its adaptive replacement cache (ARC) cache with a most recently used (MRU) and most frequently used (MFU) list. == References == == External links == Frecency implementation in


id: fudge-factor-20260505-0
file: data/en.wikipedia.org/wiki/Fudge_factor-0.md
category: reference
title: Fudge factor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fudge_factor
date_saved: 2026-05-05T09:57:45.370479+00:00
instance: kb-cron
parent: fudge-factor-20260505-0
summary:
A fudge factor is an ad hoc quantity or element introduced into a calculation, formula or model in order to make it fit observations or expectations. Also known as a correction coefficient, which is defined by κ c = experimental value theoretical value . {\displaystyle \kappa _{\text{c}}={\frac {\text{experimental value}}{\text{theoretical value}}}.} Examples include Einstein's cosmological constant, dark energy, the initial proposals of dark matter and inflation. == Examples in science == Some quantities in scientific theory are set arbitrarily according to measured results rather than by calculation (for example, the Planck constant). However, in the case of these fundamental constants, their arbitrariness is usually explicit. To suggest that other calculations may include a "fudge factor" may suggest that the calculation has been somehow tampered with to make results give a misleadingly good match to experimental data. === Cosmological constant === In theoretical physics, when Albert Einstein originally tried to produce a general theory of relativity, he found that the theory seemed to predict the gravitational collapse of the universe: it seemed that the universe should be collapsing, and to produce a model in which the universe was static and stable (which seemed to Einstein at the time to be the "proper"


id: gaze-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Gaze_heuristic-0.md
category: reference
title: Gaze heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Gaze_heuristic
date_saved: 2026-05-05T09:57:46.563786+00:00
instance: kb-cron
parent: gaze-heuristic-20260505-0
summary:
The gaze heuristic falls under the category of tracking heuristics, and it is used in directing correct motion to achieve a goal using one main variable. McLeod & Dienes' (1996) example of the gaze heuristic is catching a ball. Gerd Gigerenzer categorizes the gaze heuristic under tracking heuristics, where human animals and non-human animals are able to process large amounts of information quickly and react, regardless of whether the information is consciously processed. The gaze heuristic is a critical element in animal behavior, being used in predation heavily. At the most basic level, the gaze heuristic ignores all casual relevant variables to make quick gut reactions. == Example == A catcher using the gaze heuristic observes the initial angle of the ball and runs towards it in such a way as to keep this angle constant. The gaze heuristic does not require knowledge of any of the variables required by the optimizing approach, nor does it require the catcher to integrate information, yet it allows the catcher to catch the ball. The gaze heuristic may therefore be described at ecologically rational at least in the simple case of catching a ball in the air. == See also == Constant bearing,


id: graduated-optimization-20260505-0
file: data/en.wikipedia.org/wiki/Graduated_optimization-0.md
category: reference
title: Graduated optimization
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Graduated_optimization
date_saved: 2026-05-05T09:57:47.716297+00:00
instance: kb-cron
parent: graduated-optimization-20260505-0
summary:
Graduated optimization is a global optimization technique that attempts to solve a difficult optimization problem by initially solving a greatly simplified problem, and progressively transforming that problem (while optimizing) until it is equivalent to the difficult optimization problem. == Technique description == Graduated optimization is an improvement to hill climbing that enables a hill climber to avoid settling into local optima. It breaks a difficult optimization problem into a sequence of optimization problems, such that the first problem in the sequence is convex (or nearly convex), the solution to each problem gives a good starting point to the next problem in the sequence, and the last problem in the sequence is the difficult optimization problem that it ultimately seeks to solve. Often, graduated optimization gives better results than simple hill climbing. Further, when certain conditions exist, it can be shown to find an optimal solution to the final problem in the sequence. These conditions are: The first optimization problem in the sequence can be solved given the initial starting point. The locally convex region around the global optimum of each problem in the sequence includes the point that corresponds to the global optimum of the previous problem in the sequence.


id: guided-local-search-20260505-0
file: data/en.wikipedia.org/wiki/Guided_local_search-0.md
category: reference
title: Guided local search
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Guided_local_search
date_saved: 2026-05-05T09:57:48.899341+00:00
instance: kb-cron
parent: guided-local-search-20260505-0
summary:
Guided local search is a metaheuristic search method. A meta-heuristic method is a method that sits on top of a local search algorithm to change its behavior. Guided local search builds up penalties during a search. It uses penalties to help local search algorithms escape from local minima and plateaus. When the given local search algorithm settles in a local optimum, GLS modifies the objective function using a specific scheme (explained below). Then the local search will operate using an augmented objective function, which is designed to bring the search out of the local optimum. The key is in the way that the objective function is modified. The method in its current form was developed by Dr Christos Voudouris and detailed in his PhD Thesis. GLS was inspired by and extended GENET, a neural network architecture for solving Constraint Satisfaction Problems, which was developed by Chang Wang, Edward Tsang and Andrew Davenport. Both GLS's and GENET's mechanism for escaping from local minima resembles reinforcement learning. == Overview == === Solution features === To apply GLS, solution features must be defined for the given problem. Solution features are defined to distinguish between solutions with different characteristics, so that regions of similarity


id: guided-local-search-20260505-1
file: data/en.wikipedia.org/wiki/Guided_local_search-1.md
category: reference
title: Guided local search
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Guided_local_search
date_saved: 2026-05-05T09:57:48.899341+00:00
instance: kb-cron
parent: guided-local-search-20260505-0
summary:
== Bibliography == Alsheddy, A., Empowerment scheduling: a multi-objective optimization approach using Guided Local Search, PhD Thesis, School of Computer Science and Electronic Engineering, University of Essex, 2011 Choi, K.M.F., Lee, J.H.M. & Stuckey, P.J., A Lagrangian Resconstruction of GENET, Artificial Intelligence, 2000, 123(1-2), 1-39 Davenport A., Tsang E.P.K., Kangmin Zhu & C J Wang, GENET: A connectionist architecture for solving constraint satisfaction problems by iterative improvement, Proc., AAAI, 1994, p. 325-330 Lau, T.L. & Tsang, E.P.K., Solving the processor configuration problem with a mutation-based genetic algorithm, International Journal on Artificial Intelligence Tools (IJAIT), World Scientific, Vol.6, No.4, December 1997, 567-585 Lau, T.L. & Tsang, E.P.K., Guided genetic algorithm and its application to radio link frequency assignment problems, Constraints, Vol.6, No.4, 2001, 373-398 Lau, T.L. & Tsang, E.P.K., The guided genetic algorithm and its application to the general assignment problems, IEEE 10th International Conference on Tools with Artificial Intelligence (ICTAI'98), Taiwan, November 1998 Mills, P. & Tsang, E.P.K., Guided local search for solving SAT and weighted MAX-SAT problems, Journal of Automated Reasoning, Special Issue on Satisfiability Problems, Kluwer, Vol.24, 2000, 205-223 Mills, P. & Tsang, E.P.K. & Ford, J., Applying an Extended Guided Local Search on the Quadratic Assignment Problem,


id: heroic-theory-of-invention-and-scientific-development-20260505-0
file: data/en.wikipedia.org/wiki/Heroic_theory_of_invention_and_scientific_development-0.md
category: reference
title: Heroic theory of invention and scientific development
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heroic_theory_of_invention_and_scientific_development
date_saved: 2026-05-05T09:57:50.131628+00:00
instance: kb-cron
parent: heroic-theory-of-invention-and-scientific-development-20260505-0
summary:
The heroic theory of invention and scientific development is the view that the principal authors of inventions and scientific discoveries are unique heroic individuals—i.e., "great scientists" or "geniuses". == Competing hypothesis == A competing hypothesis (that of multiple discovery) is that most inventions and scientific discoveries are made independently and simultaneously by multiple inventors and scientists. The multiple-discovery hypothesis may be most patently exemplified in the evolution of mathematics, since mathematical knowledge is highly unified and any advances need, as a general rule, to be built from previously established results through a process of deduction. Thus, the development of infinitesimal calculus into a systematic discipline did not occur until the development of analytic geometry, the former being credited to both Sir Isaac Newton and Gottfried Leibniz, and the latter to both René Descartes and Pierre de Fermat. == See also == Genius Great man theory Grand narrative Hive mind List of multiple discoveries Multiple discovery People known as the father or mother of something Scientific priority Scientific theory Discovery and invention controversies == References == == Further reading == Epstein, Ralph C. 1926. "Industrial Invention: Heroic, or Systematic?" The Quarterly Journal of Economics 40(2):232–72. JSTOR 1884619. doi:10.2307/1884619. Johansson, Frans. 2004.


id: heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Heuristic-0.md
category: reference
title: Heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic
date_saved: 2026-05-05T09:57:51.251656+00:00
instance: kb-cron
parent: heuristic-20260505-0
summary:
A heuristic or heuristic technique (problem solving, mental shortcut, rule of thumb) is any approach to problem solving that employs a pragmatic method that is not fully optimized, perfected, or rationalized, but is nevertheless "good enough" as an approximation or attribute substitution. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision. Heuristic reasoning is often based on induction, or on analogy ... Induction is the process of discovering general laws ... Induction tries to find regularity and coherence ... Its most conspicuous instruments are generalization, specialization, analogy. [...] Heuristic discusses human behavior in the face of problems [... that have been] preserved in the wisdom of proverbs. == Context == Gigerenzer & Gaissmaier (2011) state that sub-sets of strategy include heuristics, regression analysis, and Bayesian inference. A heuristic is a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods... Heuristics are strategies based on rules to generate optimal decisions, like the anchoring effect and utility maximization problem. These


id: heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Heuristic-1.md
category: reference
title: Heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic
date_saved: 2026-05-05T09:57:51.251656+00:00
instance: kb-cron
parent: heuristic-20260505-0
summary:
=== Adaptive toolbox === The adaptive toolbox contains strategies for fabricating heuristic devices. The core mental capacities are recall (memory), frequency, object permanence, and imitation. Gerd Gigerenzer and his research group argued that models of heuristics need to be formal to allow for predictions of behavior that can be tested. They study the fast and frugal heuristics in the "adaptive toolbox" of individuals or institutions, and the ecological rationality of these heuristics; that is, the conditions under which a given heuristic is likely to be successful. The descriptive study of the "adaptive toolbox" is done by observation and experiment, while the prescriptive study of ecological rationality requires mathematical analysis and computer simulation. Heuristics – such as the recognition heuristic, the take-the-best heuristic and fast-and-frugal trees – have been shown to be effective in predictions, particularly in situations of uncertainty. It is often said that heuristics trade accuracy for effort but this is only the case in situations of risk. Risk refers to situations where all possible actions, their outcomes and probabilities are known. In the absence of this information, that is under uncertainty, heuristics can achieve higher accuracy with lower effort. This finding, known as a less-is-more effect, would not


id: heuristic-20260505-2
file: data/en.wikipedia.org/wiki/Heuristic-2.md
category: reference
title: Heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic
date_saved: 2026-05-05T09:57:51.251656+00:00
instance: kb-cron
parent: heuristic-20260505-0
summary:
=== Law === In legal theory, especially in the theory of law and economics, heuristics are used in the law when case-by-case analysis would be impractical, insofar as "practicality" is defined by the interests of a governing body. The present securities regulation regime largely assumes that all investors act as perfectly rational persons. In truth, actual investors face cognitive limitations from biases, heuristics, and framing effects. For instance, in all states in the United States the legal drinking age for unsupervised persons is 21 years, because it is argued that people need to be mature enough to make decisions involving the risks of alcohol consumption. However, assuming people mature at different rates, the specific age of 21 would be too late for some and too early for others. In this case, the somewhat arbitrary delineation is used because it is impossible or impractical to tell whether an individual is sufficiently mature for society to trust them with that kind of responsibility. Some proposed changes, however, have included the completion of an alcohol education course rather than the attainment of 21 years of age as the criterion for legal alcohol possession. This would put youth alcohol policy more on a case-by-case


id: heuristic-20260505-3
file: data/en.wikipedia.org/wiki/Heuristic-3.md
category: reference
title: Heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic
date_saved: 2026-05-05T09:57:51.251656+00:00
instance: kb-cron
parent: heuristic-20260505-0
summary:
ACT-R – SoftwarePages displaying short descriptions with no spaces Algorithm – Sequence of operations for a task Applied epistemology – Application of epistemology in specific fields Branch and bound – Optimization by removing non-optimal solutions to subproblems Coherence (philosophical gambling strategy) – Thought experiment, to justify Bayesian probabilityPages displaying short descriptions of redirect targets Decision theory – Branch of applied probability theory Embodied cognition – Interdisciplinary theory Failure mode and effects analysis – Analysis of potential system failures Game theory – Mathematical models of strategic interactions Heuristic-systematic model of information processing – Dual-process theory of persuasion Heuristics in judgment and decision-making – Simple strategies or mental processes involved in making quick decisionsPages displaying short descriptions of redirect targets Ideal type – Typological term List of biases in judgment and decision making Metalepsis – Figure of speech Methodic school – School of medicine in ancient Greece and Rome Necessity and sufficiency – Terms to describe a conditional relationship between two statements Neuroheuristics Nudge theory – Concept in behavioral economics, political theory and behavioral sciences Predictive coding – Theory of brain function Principle of good enough – Principle of social research Priority heuristic – Decision strategy Prospect theory – Theory of behavioral


id: heuristic-psychology-20260505-0
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-0.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
Heuristics (from Ancient Greek εὑρίσκω (heurískō) 'to find, discover') is the process by which humans use mental shortcuts to arrive at decisions. Heuristics are simple strategies that humans, animals, organizations, and even machines use to quickly form judgments, make decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution. While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. In that sense they can differ from answers given by logic and probability. The economist and cognitive psychologist Herbert A. Simon introduced the concept of heuristics in the 1950s, suggesting there were limitations to rational decision making. In the 1970s, psychologists Amos Tversky and Daniel Kahneman added to the field with their research on cognitive bias. It was their work that introduced specific heuristic models, a field which has only expanded since. While some argue that pure laziness is behind the heuristics process, this


id: heuristic-psychology-20260505-1
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-1.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
Step 1: Select one attribute related to decision making Step 2: Eliminate all alternatives that exclude this specific attribute Step 3: Use another attribute in order to further eliminate alternatives Step 4: Repeat step 3 until only one option is left, a decision has then been made Elimination by aspects does not speculate that choosing alternatives could help consumers to maximize utility, on the contrary, it holds that selection is the result of a probabilistic process that gradually eliminates alternatives. A simple example is given by Amos Tversky: when someone wants to purchase a new car, the first aspect they will take into account might be the automatic transmission, this will eliminate all alternatives that do not contain such an aspect. Then, when all the alternatives that do not have this feature are eliminated, another aspect will be given such as a $3000 price limit. The process of elimination continues to occur until all alternatives are eliminated. Elimination by aspects is well used in the early stage of business angels' decision-making process since it facilitates a fast-decision-making tool - alternatives will be eliminated when investors find a critical defect of the potential opportunities. Another research also demonstrated that elimination by


id: heuristic-psychology-20260505-2
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-2.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
In the HIV tree, an ELISA (enzyme-linked immunosorbent assay) test is conducted first. If the outcome is negative, then the testing procedure stops and the client is informed of the good news, that is, "no HIV." If, however, the result is positive, a second ELISA test is performed, preferably from a different manufacturer. If the second ELISA is negative, then the procedure stops and the client is informed of having "no HIV." However, if the result is positive, a final test, the Western blot, is conducted. In general, for n binary cues, a fast-and-frugal tree has exactly n + 1 exits – one for each cue and two for the final cue. A full decision tree, in contrast, requires 2n exits. The order of cues (tests) in a fast-and-frugal tree is determined by the sensitivity and specificity of the cues, or by other considerations such as the costs of the tests. In the case of the HIV tree, the ELISA is ranked first because it produces fewer misses than the Western blot test, and also is less expensive. The Western blot test, in contrast, produces fewer false alarms. In a full tree, in contrast, order does not matter for the


id: heuristic-psychology-20260505-3
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-3.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
Affect heuristic: A mental shortcut which uses emotion to influence the decision. Emotion is the effect that plays the lead role that makes the decision or solves the problem quickly or efficiently. It is used while judging the risks and benefits of something, depending on the positive or negative feelings that people associate with a stimulus. It can also be considered the gut decision since if the gut feeling is right, then the benefits are high and the risks are low. Anchoring and adjustment: Describes the common human tendency to rely more heavily on the first piece of information offered (the "anchor") when making decisions. For example, in a study done with children, the children were told to estimate the number of jellybeans in a jar. Groups of children were given either a high or low "base" number (anchor). Children estimated the number of jellybeans to be closer to the anchor number that they were given. Availability heuristic: A mental shortcut that occurs when people make judgements about the probability of events by the ease with which examples come to mind. For example, in a 1973 Tversky & Kahneman experiment, the majority of participants reported that there were more words


id: heuristic-psychology-20260505-4
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-4.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
People regret the events that are easier to imagine over the ones that would be harder to. It is also thought that people will use this heuristic to predict the likelihood of another's behavior happening. This shows that people are constantly simulating everything around them in order to be able to predict the likelihood of events around them. It is believed that people do this by mentally undoing events that they have experienced and then running mental simulations of the events with the corresponding input values of the altered model. Social proof: Also known as the informational social influence which was named by Robert Cialdini in his 1984 book Influence. It is where people copy the actions of others. It is more prominent when people are uncertain how to behave, especially in ambiguous social situations. Working backward heuristic: When an individual assumes they have already solved a problem they work backwards in order to find how to achieve the solution they originally figured out.


id: heuristic-psychology-20260505-5
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-5.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
=== Availability === In psychology, availability is the ease with which a particular idea can be brought to mind. When people estimate how likely or how frequent an event is on the basis of its availability, they are using the availability heuristic. When an infrequent event can be brought easily and vividly to mind, this heuristic overestimates its likelihood. For example, people overestimate their likelihood of dying in a dramatic event such as a tornado or terrorism. Dramatic, violent deaths are usually more highly publicised and therefore have a higher availability. On the other hand, common but mundane events are hard to bring to mind, so their likelihoods tend to be underestimated. These include deaths from suicides, strokes, and diabetes. This heuristic is one of the reasons why people are more easily swayed by a single, vivid story than by a large body of statistical evidence. It may also play a role in the appeal of lotteries: to someone buying a ticket, the well-publicised, jubilant winners are more available than the millions of people who have won nothing. When people judge whether more English words begin with T or with K , the availability heuristic gives a quick way to


id: heuristic-psychology-20260505-6
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-6.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
A 1973 experiment used a psychological profile of Tom W., a fictional graduate student. One group of subjects had to rate Tom's similarity to a typical student in each of nine academic areas (including Law, Engineering and Library Science). Another group had to rate how likely it is that Tom specialised in each area. If these ratings of likelihood are governed by probability, then they should resemble the base rates, i.e. the proportion of students in each of the nine areas (which had been separately estimated by a third group). If people based their judgments on probability, they would say that Tom is more likely to study Humanities than Library Science, because there are many more Humanities students, and the additional information in the profile is vague and unreliable. Instead, the ratings of likelihood matched the ratings of similarity almost perfectly, both in this study and a similar one where subjects judged the likelihood of a fictional woman taking different careers. This suggests that rather than estimating probability using base rates, subjects had substituted the more accessible attribute of similarity. ==== Conjunction fallacy ==== When people rely on representativeness, they can fall into an error which breaks a fundamental law


id: heuristic-psychology-20260505-7
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-7.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
==== Misperception of randomness ==== Representativeness explains systematic errors that people make when judging the probability of random events. For example, in a sequence of coin tosses, each of which comes up heads (H) or tails (T), people reliably tend to judge a clearly patterned sequence such as HHHTTT as less likely than a less patterned sequence such as HTHTTH. These sequences have exactly the same probability, but people tend to see the more clearly patterned sequences as less representative of randomness, and so less likely to result from a random process. Tversky and Kahneman argued that this effect underlies the gambler's fallacy; a tendency to expect outcomes to even out over the short run, like expecting a roulette wheel to come up black because the last several throws came up red. They emphasised that even experts in statistics were susceptible to this illusion: in a 1971 survey of professional psychologists, they found that respondents expected samples to be overly representative of the population they were drawn from. As a result, the psychologists systematically overestimated the statistical power of their tests, and underestimated the sample size needed for a meaningful test of their hypotheses. === Anchoring and adjustment === Anchoring


id: heuristic-psychology-20260505-8
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-8.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
==== Examples ==== People's valuation of goods, and the quantities they buy, respond to anchoring effects. In one experiment, people wrote down the last two digits of their social security numbers. They were then asked to consider whether they would pay this number of dollars for items whose value they did not know, such as wine, chocolate, and computer equipment. They then entered an auction to bid for these items. Those with the highest two-digit numbers submitted bids that were many times higher than those with the lowest numbers. When a stack of soup cans in a supermarket was labelled, "Limit 12 per customer", the label influenced customers to buy more cans. In another experiment, real estate agents appraised the value of houses on the basis of a tour and extensive documentation. Different agents were shown different listing prices, and these affected their valuations. For one house, the appraised value ranged from US$114,204 to $128,754. Anchoring and adjustment has also been shown to affect grades given to students. In one experiment, 48 teachers were given bundles of student essays, each of which had to be graded and returned. They were also given a fictional list of the students' previous grades.


id: heuristic-psychology-20260505-9
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-9.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
An effort-reduction framework proposed by Anuj K. Shah and Daniel M. Oppenheimer states that people use a variety of techniques to reduce the effort of making decisions. === Attribute substitution === In 2002 Daniel Kahneman and Shane Frederick proposed a process called attribute substitution which happens without conscious awareness. According to this theory, when somebody makes a judgment (of a target attribute) which is computationally complex, a rather more easily calculated heuristic attribute is substituted. In effect, a difficult problem is dealt with by answering a rather simpler problem, without the person being aware this is happening. This explains why individuals can be unaware of their own biases, and why biases persist even when the subject is made aware of them. It also explains why human judgments often fail to show regression toward the mean. This substitution is thought of as taking place in the automatic intuitive judgment system, rather than the more self-aware reflective system. Hence, when someone tries to answer a difficult question, they may actually answer a related but different question, without realizing that a substitution has taken place. In 1975, psychologist Stanley Smith Stevens proposed that the strength of a stimulus (e.g. the brightness of a


id: heuristic-psychology-20260505-10
file: data/en.wikipedia.org/wiki/Heuristic_(psychology)-10.md
category: reference
title: Heuristic (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_(psychology)
date_saved: 2026-05-05T09:57:52.503423+00:00
instance: kb-cron
parent: heuristic-psychology-20260505-0
summary:
=== Persuasion === An example of how persuasion plays a role in heuristic processing can be explained through the heuristic-systematic model. This explains how there are often two ways we are able to process information from persuasive messages, one being heuristically and the other systematically. A heuristic is when we make a quick short judgement into our decision making. On the other hand, systematic processing involves more analytical and inquisitive cognitive thinking. Individuals looks further than their own prior knowledge for the answers. An example of this model could be used when watching an advertisement about a specific medication. One without prior knowledge would see the person in the proper pharmaceutical attire and assume that they know what they are talking about. Therefore, that person automatically has more credibility and is more likely to trust the content of the messages than they deliver. While another who is also in that field of work or already has prior knowledge of the medication will not be persuaded by the ad because of their systematic way of thinking. This was also formally demonstrated in an experiment conducted by Chaiken and Maheswaran (1994). In addition to these examples, the fluency heuristic ties in perfectly


id: heuristic-argument-20260505-0
file: data/en.wikipedia.org/wiki/Heuristic_argument-0.md
category: reference
title: Heuristic argument
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic_argument
date_saved: 2026-05-05T09:57:53.744118+00:00
instance: kb-cron
parent: heuristic-argument-20260505-0
summary:
A heuristic argument is an argument that reasons from the value of a method or principle that has been shown experimentally (especially through trial-and-error) to be useful or convincing in learning, discovery and problem-solving, but whose line of reasoning involves key oversimplifications that make it not entirely rigorous. A widely used and important example of a heuristic argument is Occam's razor. It is a speculative, non-rigorous argument that relies on analogy or intuition, and that allows one to achieve a result or an approximation that is to be checked later with more rigor. Otherwise, the results are generally to be doubted. It is used as a hypothesis or a conjecture in an investigation, though it can also be used as a mnemonic as well. == See also == Empirical relationship Heuristic Probabilistic method Rule of thumb == References ==


id: heuristic-systematic-model-of-information-processing-20260505-0
file: data/en.wikipedia.org/wiki/Heuristic-systematic_model_of_information_processing-0.md
category: reference
title: Heuristic-systematic model of information processing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic-systematic_model_of_information_processing
date_saved: 2026-05-05T09:57:54.948181+00:00
instance: kb-cron
parent: heuristic-systematic-model-of-information-processing-20260505-0
summary:
The heuristic-systematic model of information processing (HSM) is a widely recognized model by Shelly Chaiken that attempts to explain how people receive and process persuasive messages. The model states that individuals can process messages in one of two ways: heuristically or systematically. Systematic processing entails careful and deliberative processing of a message, while heuristic processing entails the use of simplifying decision rules or 'heuristics' to quickly assess the message content. The guiding belief with this model is that individuals are more apt to minimize their use of cognitive resources (i.e., to rely on heuristics), thus affecting the intake and processing of messages. HSM predicts that processing type will influence the extent to which a person is persuaded or exhibits lasting attitude change. HSM is quite similar to the elaboration likelihood model, or ELM. Both models were predominantly developed in the early- to mid-1980s and share many of the same concepts and ideas. == History == Early research investigating how people process persuasive messaging focused mainly on cognitive theories and the way the mind processed each element of a message. One of the early guiding principles of underlying motivations of persuasive communications came from Leon Festinger's (1950) statement that incorrect or


id: heuristic-systematic-model-of-information-processing-20260505-1
file: data/en.wikipedia.org/wiki/Heuristic-systematic_model_of_information_processing-1.md
category: reference
title: Heuristic-systematic model of information processing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic-systematic_model_of_information_processing
date_saved: 2026-05-05T09:57:54.948181+00:00
instance: kb-cron
parent: heuristic-systematic-model-of-information-processing-20260505-0
summary:
== Choosing systematic or heuristic processing == Both heuristic and systematic processes may occur independently. It is also possible for both to occur simultaneously in an additive fashion or in a way that the judgmental implications of one process lend a bias nature to the other. The heuristic-systematic model includes the hypothesis that attitudes developed or changed by utilizing heuristic processing alone will likely be less stable, less resistant to counterarguments, and will be less predictive of subsequent behavior than attitudes developed or changed utilizing systematic processing. Message recipients using heuristic processing may sometimes choose to accept message conclusions they would otherwise have rejected, or vice versa, had they invested more time and effort to scrutinize the message. Source credibility affects persuasion under conditions of low, but not high, issue-involvement and response-involvement. When economic concerns are predominant, the recipient will likely use heuristic processing to form a judgement about the persuasive argument. Conversely, when reliability concerns are predominant (i.e., recipients perceive significant importance in accurately judging an argument), they will likely use a systematic processing strategy. Reliability concerns are influenced by the level of the recipient's issue-involvement or response-involvement. When the recipient views their judgment as being less consequential, they


id: heuristic-systematic-model-of-information-processing-20260505-2
file: data/en.wikipedia.org/wiki/Heuristic-systematic_model_of_information_processing-2.md
category: reference
title: Heuristic-systematic model of information processing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Heuristic-systematic_model_of_information_processing
date_saved: 2026-05-05T09:57:54.948181+00:00
instance: kb-cron
parent: heuristic-systematic-model-of-information-processing-20260505-0
summary:
== Criticisms == A major criticism of HSM is that the model closely relates to ELM, which is also a dual-processing model discussing two main paths to persuasion. The ELM discusses the two routes as "central" route processing and "peripheral" route processing. ELM's central processing has been likened to systematic processing in HSM, while peripheral processing is similar to HSM's heuristic processing. These two routes of processing define related theories behind attitude change. In ELM, the central route is reflective and requires a willingness to process and think about the message. The peripheral route occurs when attitudes are formed without extensive thought, but more from mental shortcuts, credibility, and appearance cues. The route of persuasion processing depends on the level of involvement in the topic or issue. High involvement or elaboration increases central route processing especially when motivation and ability in the message exists. Therefore, low involvement increases peripheral route processing when motivation and ability conditions of persuasion do not exist. However, if the topic or idea is irrelevant to the individual, then the message takes the peripheral route. HSM specifically examines validity seeking persuasion settings concerning people's motivations within the social environment. The limitation of HSM exists in the


id: hitchens-s-razor-20260505-0
file: data/en.wikipedia.org/wiki/Hitchens's_razor-0.md
category: reference
title: Hitchens's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hitchens's_razor
date_saved: 2026-05-05T09:57:56.122921+00:00
instance: kb-cron
parent: hitchens-s-razor-20260505-0
summary:
Hitchens's razor is a general rule for rejecting certain claims of knowledge. It states: What can be asserted without evidence can also be dismissed without evidence. The razor is credited to author and journalist Christopher Hitchens, although its provenance can be traced to the Latin Quod gratis asseritur, gratis negatur ("What is asserted gratuitously is denied gratuitously"). It implies that the burden of proof regarding the truthfulness of a claim lies with the one who makes the claim; if this burden is not met, then the claim is unfounded, and its opponents need not argue further in order to dismiss it. Hitchens used this phrase specifically in the context of refuting religious belief. == Analysis == The epistemological dictum appears in Hitchens's 2007 book God Is Not Great: How Religion Poisons Everything. The term "Hitchens's razor" itself first appeared (as "Hitchens' razor") in an online forum in October 2007, and was used by atheist blogger Rixaeton in December 2010, and popularised by, among others, evolutionary biologist and atheist activist Jerry Coyne after Hitchens died in December 2011. Some pages earlier in God Is Not Great, Hitchens also invoked Occam's razor. William Ockham devised a principle of economy, popularly known as


id: how-to-solve-it-20260505-0
file: data/en.wikipedia.org/wiki/How_to_Solve_It-0.md
category: reference
title: How to Solve It
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/How_to_Solve_It
date_saved: 2026-05-05T09:57:57.303829+00:00
instance: kb-cron
parent: how-to-solve-it-20260505-0
summary:
How to Solve It (1945) is a small volume by mathematician George Pólya, describing methods of problem solving. This book has remained in print continually since 1945. == Four principles == How to Solve It suggests the following steps when solving a mathematical problem: First, you have to understand the problem. After understanding, make a plan. Carry out the plan. Look back on your work. How could it be better? If this technique fails, Pólya advises: "If you cannot solve the proposed problem, try to solve first some related problem. Could you imagine a more accessible related problem?" === First principle: Understand the problem === "Understand the problem" is often neglected as being obvious and is not even mentioned in many mathematics classes. Yet students are often stymied in their efforts to solve it, simply because they don't understand it fully, or even in part. In order to remedy this oversight, Pólya taught teachers how to prompt each student with appropriate questions, depending on the situation, such as: What are you asked to find or show? Can you restate the problem in your own words? Can you think of a picture or a diagram that might help you understand the


id: how-to-solve-it-by-computer-20260505-0
file: data/en.wikipedia.org/wiki/How_to_Solve_it_by_Computer-0.md
category: reference
title: How to Solve it by Computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/How_to_Solve_it_by_Computer
date_saved: 2026-05-05T09:57:58.541393+00:00
instance: kb-cron
parent: how-to-solve-it-by-computer-20260505-0
summary:
How to Solve it by Computer is a computer science book by R. G. Dromey, first published by Prentice-Hall in 1982. It is occasionally used as a textbook, especially in India. It is an introduction to the whys of algorithms and data structures. Features of the book: The design factors associated with problems, The creative process behind coming up with innovative solutions for algorithms and data structures, The line of reasoning behind the constraints, factors and the design choices made. The very fundamental algorithms portrayed by this book are mostly presented in pseudocode and/or Pascal notation. == See also == How to Solve It, by George Pólya, the author's mentor and inspiration for writing the book. == References ==


id: hyper-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Hyper-heuristic-0.md
category: reference
title: Hyper-heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hyper-heuristic
date_saved: 2026-05-05T09:57:59.680477+00:00
instance: kb-cron
parent: hyper-heuristic-20260505-0
summary:
A hyper-heuristic is a heuristic search method that seeks to automate, often by the incorporation of machine learning techniques, the process of selecting, combining, generating or adapting several simpler heuristics (or components of such heuristics) to efficiently solve computational search problems. One of the motivations for studying hyper-heuristics is to build systems which can handle classes of problems rather than solving just one problem. There might be multiple heuristics from which one can choose for solving a problem, and each heuristic has its own strength and weakness. The idea is to automatically devise algorithms by combining the strength and compensating for the weakness of known heuristics. In a typical hyper-heuristic framework there is a high-level methodology and a set of low-level heuristics (either constructive or perturbative heuristics). Given a problem instance, the high-level method selects which low-level heuristic should be applied at any given time, depending upon the current problem state (or search stage) determined by features. == Hyper-heuristics versus metaheuristics == The fundamental difference between metaheuristics and hyper-heuristics is that most implementations of metaheuristics search within a search space of problem solutions, whereas hyper-heuristics always search within a search space of heuristics. Thus, when using hyper-heuristics, we are attempting


id: hyper-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Hyper-heuristic-1.md
category: reference
title: Hyper-heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hyper-heuristic
date_saved: 2026-05-05T09:57:59.680477+00:00
instance: kb-cron
parent: hyper-heuristic-20260505-0
summary:
=== Methodologies to choose heuristics === Discover good combinations of fixed, human-designed, well-known low-level heuristics. Based on constructive heuristics Based on perturbative heuristics === Methodologies to generate heuristics === Generate new heuristic methods using basic components of previously existing heuristic methods. Based on basic components of constructive heuristics Based on basic components of perturbative heuristics === On-line learning hyper-heuristics === The learning takes place while the algorithm is solving an instance of a problem, therefore, task-dependent local properties can be used by the high-level strategy to determine the appropriate low-level heuristic to apply. Examples of on-line learning approaches within hyper-heuristics are: the use of reinforcement learning for heuristic selection, and generally the use of metaheuristics as high-level search strategies over a search space of heuristics. === Off-line learning hyper-heuristics === The idea is to gather knowledge in form of rules or programs, from a set of training instances, which would hopefully generalise to the process of solving unseen instances. Examples of off-line learning approaches within hyper-heuristics are: learning classifier systems, case-base reasoning and genetic programming. An extended classification of selection hyper-heuristics was provided in 2020, to provide a more comprehensive categorisation of contemporary selection hyper-heuristic methods. == Applications == Hyper-heuristics


id: killer-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Killer_heuristic-0.md
category: reference
title: Killer heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Killer_heuristic
date_saved: 2026-05-05T09:58:00.836666+00:00
instance: kb-cron
parent: killer-heuristic-20260505-0
summary:
In competitive two-player games, the killer heuristic is a move-ordering method based on the observation that a strong move or small set of such moves in a particular position may be equally strong in similar positions at the same move (ply) in the game tree. Retaining such moves obviates the effort of rediscovering them in sibling nodes. This technique improves the efficiency of alpha–beta pruning, which in turn improves the efficiency of the minimax algorithm. Alpha–beta pruning works best when the best moves are considered first. This is because the best moves are the ones most likely to produce a cutoff, a condition where the game-playing program knows that the position it is considering could not possibly have resulted from best play by both sides and so need not be considered further. I.e. the game-playing program will always make its best available move for each position. It only needs to consider the other player's possible responses to that best move, and can skip evaluation of responses to (worse) moves it will not make. The killer heuristic attempts to produce a cutoff by assuming that a move that produced a cutoff in another branch of the game tree at the same


id: knowledge-inertia-20260505-0
file: data/en.wikipedia.org/wiki/Knowledge_inertia-0.md
category: reference
title: Knowledge inertia
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Knowledge_inertia
date_saved: 2026-05-05T09:58:02.012633+00:00
instance: kb-cron
parent: knowledge-inertia-20260505-0
summary:
Knowledge inertia (KI) is a concept in knowledge management. The term initially proposed by Shu-hsien Liao comprises a two dimensional model which incorporates experience inertia and learning inertia. Later, another dimension—the dimension of thinking inertia—has been added based on the theoretical exploration of the existing concepts of experience inertia and learning inertia. One of the central problems in knowledge management related to organizational learning is to deal with "inertia". Besides, individuals may also exhibit a natural tendency of inertia when facing problems during utilization of knowledge. Inertia in technical jargon means inactivity or torpor. Inertia in organizational learning context may be referred to as a slowdown in organizational learning-related activities. In fact, there are many other kinds of organizational inertia: e.g., innovation inertia, workforce inertia, productivity inertia, decision inertia, emotional inertia besides others that have different meanings in their own individual contexts. Some organization theorists have adopted the definition proposed by Liao (2002) to extend its further use in organizational learning studies. == Definition == Knowledge inertia (KI) may be defined as a problem solving strategy using old, redundant, stagnant knowledge and past experience without recourse to new knowledge and experience. Inertia is a concept in physics that is used


id: lectio-difficilior-potior-20260505-0
file: data/en.wikipedia.org/wiki/Lectio_difficilior_potior-0.md
category: reference
title: Lectio difficilior potior
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Lectio_difficilior_potior
date_saved: 2026-05-05T09:58:03.182623+00:00
instance: kb-cron
parent: lectio-difficilior-potior-20260505-0
summary:
Lectio difficilior potior (Latin: "the difficult reading is stronger") is an important, internal criterion in textual criticism. When different manuscripts of a text conflict, this principle requires that the harder, unusual, more obtuse reading is to be preferred. It is based on the assumption that scribes are more likely to replace odd words in difficult places with more familiar vocabulary in more expected positions. It was one principle among many that became established in early 18th-century textual criticism, being part of an attempt by scholars of the Age of Enlightenment to provide a neutral basis for discovering an urtext that was independent of the weight of traditional authority. == History == Rabbeinu Tam (1100 – 1171) expressed the idea in his midrash The Book of Jasher (Heb. ספר הישר, Sefer haYashar), it was written by the author of the Talmud, since students who correct the text do not correct it in order to make the text difficult. Erasmus expressed the idea in his Annotations to the New Testament in the early 1500s, And whenever the Fathers report that there is a variant reading, that one always appears to me to be more esteemed (by them is the one) which at


id: littlewood-s-three-principles-of-real-analysis-20260505-0
file: data/en.wikipedia.org/wiki/Littlewood's_three_principles_of_real_analysis-0.md
category: reference
title: Littlewood's three principles of real analysis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Littlewood's_three_principles_of_real_analysis
date_saved: 2026-05-05T09:58:04.321104+00:00
instance: kb-cron
parent: littlewood-s-three-principles-of-real-analysis-20260505-0
summary:
Littlewood's three principles of real analysis are heuristics of J. E. Littlewood to help teach the essentials of measure theory in mathematical analysis. == The Principles == Littlewood stated the principles in his 1944 Lectures on the Theory of Functions as: There are three principles, roughly expressible in the following terms: Every (measurable) set is nearly a finite sum of intervals; every function (of class Lp) is nearly continuous; every convergent sequence of functions is nearly uniformly convergent. The first principle is based on the fact that the inner measure and outer measure are equal for measurable sets, the second is based on Lusin's theorem, and the third is based on Egorov's theorem. == Example == Littlewood's three principles are quoted in several real analysis texts, for example Royden, Bressoud, and Stein & Shakarchi. Royden gives the bounded convergence theorem as an application of the third principle. The theorem states that if a uniformly bounded sequence of functions converges pointwise, then their integrals on a set of finite measure converge to the integral of the limit function. If the convergence were uniform this would be a trivial result, and Littlewood's third principle tells us that the convergence is almost uniform,


id: m-ratio-20260505-0
file: data/en.wikipedia.org/wiki/M-ratio-0.md
category: reference
title: M-ratio
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/M-ratio
date_saved: 2026-05-05T09:58:05.470846+00:00
instance: kb-cron
parent: m-ratio-20260505-0
summary:
In no-limit or pot-limit poker, a player's M-ratio (also called "M number", "M factor" or just "M") is a measure of the health of a player's chip stack as a function of the cost to play each round. In simple terms, a player can sit passively in the game, making only compulsory bets, for M laps of the dealer button before running out of chips. A high M means the player can afford to wait a high number of rounds before making a move. The concept applies primarily in tournament poker; in a cash game, a player can in principle manipulate their M at will, simply by purchasing more chips. A player with a low M must act soon or be weakened by the inability to force other players to fold with aggressive raises. The term was named after Paul Magriel. == Calculation == The M-ratio is calculated by the formula: M = stack small blind + big blind + total antes {\displaystyle M={\frac {\mbox{stack}}{{\mbox{small blind}}+{\mbox{big blind}}+{\mbox{total antes}}}}} For example, a player in an eight-player game with blinds of $50/$100, an ante of $10, and a stack of $2,300 has an M-ratio of 10: M = 2300 50 + 100


id: maximization-psychology-20260505-0
file: data/en.wikipedia.org/wiki/Maximization_(psychology)-0.md
category: reference
title: Maximization (psychology)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Maximization_(psychology)
date_saved: 2026-05-05T09:58:06.650578+00:00
instance: kb-cron
parent: maximization-psychology-20260505-0
summary:
Maximization is a style of decision-making characterized by seeking the best option through an exhaustive search through alternatives. It is contrasted with satisficing, in which individuals evaluate options until they find one that is "good enough". == Definition == The distinction between "maximizing" and "satisficing" was first made by Herbert A. Simon in 1956. Simon noted that although fields like economics posited maximization or "optimizing" as the rational method of making decisions, humans often lack the cognitive resources or the environmental affordances to maximize. Simon instead formulated an approach known as bounded rationality, which he also referred to as satisficing. This approach was taken to be adaptive and, indeed, necessary, given our cognitive limitations. Thus, satisficing was taken to be a universal of human cognition. Although Simon's work on bounded rationality was influential and can be seen as the origin of behavioral economics, the distinction between maximizing and satisficing gained new life 40 years later in psychology. Schwartz, Ward, Monterosso, Lyubomirsky, White, and Lehman (2002) defined maximization as an individual difference, arguing that some people were more likely than others to engage in a comprehensive search for the best option. Thus, instead of conceptualizing satisficing as a universal principle of


id: meta-optimization-20260505-0
file: data/en.wikipedia.org/wiki/Meta-optimization-0.md
category: reference
title: Meta-optimization
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Meta-optimization
date_saved: 2026-05-05T09:58:07.818383+00:00
instance: kb-cron
parent: meta-optimization-20260505-0
summary:
Meta-optimization from numerical optimization is the use of one optimization method to tune another optimization method. Meta-optimization is reported to have been used as early as in the late 1970s by Mercer and Sampson for finding optimal parameter settings of a genetic algorithm. Meta-optimization and related concepts are also known in the literature as meta-evolution, super-optimization, automated parameter calibration, hyper-heuristics, etc. == Motivation == Optimization methods such as genetic algorithm and differential evolution have several parameters that govern their behaviour and efficiency in optimizing a given problem and these parameters must be chosen by the practitioner to achieve satisfactory results. Selecting the behavioural parameters by hand is a laborious task that is susceptible to human misconceptions of what makes the optimizer perform well. The behavioural parameters of an optimizer can be varied and the optimization performance plotted as a landscape. This is computationally feasible for optimizers with few behavioural parameters and optimization problems that are fast to compute, but when the number of behavioural parameters increases the time usage for computing such a performance landscape increases exponentially. This is the curse of dimensionality for the search-space consisting of an optimizer's behavioural parameters. An efficient method is therefore needed to search


id: missing-sock-20260505-0
file: data/en.wikipedia.org/wiki/Missing_sock-0.md
category: reference
title: Missing sock
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Missing_sock
date_saved: 2026-05-05T09:58:09.020749+00:00
instance: kb-cron
parent: missing-sock-20260505-0
summary:
A missing sock, lost sock, or odd sock (primarily British English) is a single sock in a pair of socks known or perceived to be permanently or temporarily missing. Socks are usually perceived to be lost immediately before, during, or immediately after doing laundry. According to popular media articles regarding missing socks, people almost always report losing one sock in a pair, and hardly ever the entire pair of two socks. Various explanations or theories—some scientific or pseudo-scientific and others humorous or facetious—have been proposed to show how or why single socks go missing or are perceived to have gone missing. The terms odd sock and mismatched sock may instead refer to the remaining "orphaned" sock in a pair where the other matching sock is missing or lost. == Plausible explanations == Two common plausible explanations for missing socks are that they are lost in transit to or from the laundry, or that they are trapped inside, between, or behind components of ("eaten by") washing machines or clothes dryers. Due to the high rotational speeds of modern front-loading washing machines and dryers, it may be possible for small clothes items such as socks to slip through any holes or tears


id: missing-sock-20260505-1
file: data/en.wikipedia.org/wiki/Missing_sock-1.md
category: reference
title: Missing sock
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Missing_sock
date_saved: 2026-05-05T09:58:09.020749+00:00
instance: kb-cron
parent: missing-sock-20260505-0
summary:
== Humorous explanations == Some explanations for the phenomenon jokingly suggest that socks have some innate propensity for going missing, and that this may be a physical property of the universe. For example, in the 1996 book The Nature of Space and Time by the physicists Stephen Hawking and Nobel laureate Roger Penrose, they posit that spontaneous black holes are responsible for lost socks. In his 2008 examination of the phenomenon, George B. Johnson also rejected two humorous hypotheses for why socks go missing: that an "intrinsic property" of the socks themselves predisposes or causes them to go missing; and that the socks transform into something else, such as clothes hangers. == In popular culture == The Bobs' 1988 song "Where Does the Wayward Footwear Go?", asks where lost socks disappear to, asking "To the bottom of the ocean? Or to China? Or to Cuba? Or Aruba?". A 1993 album by the American indie rock band Grifters is titled One Sock Missing. In the 2001 American children's film Halloweentown II: Kalabar's Revenge, lost objects including socks are magically transported to the home of a character named Gort, who is a compulsive hoarder. American illustrator and voice actor Harry S. Robins


id: money-illusion-20260505-0
file: data/en.wikipedia.org/wiki/Money_illusion-0.md
category: reference
title: Money illusion
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Money_illusion
date_saved: 2026-05-05T09:58:10.202439+00:00
instance: kb-cron
parent: money-illusion-20260505-0
summary:
In economics, money illusion, or price illusion, is a cognitive bias where money is thought of in nominal, rather than real terms. In other words, the face value (nominal value) of money is mistaken for its purchasing power (real value) at a previous point in time. Viewing purchasing power as measured by the nominal value is false, as modern fiat currencies have no intrinsic value and their real value depends purely on the price level. The term was coined by Irving Fisher in Stabilizing the Dollar. It was popularized by John Maynard Keynes in the early twentieth century, and Irving Fisher wrote an important book on the subject, The Money Illusion, in 1928. The existence of money illusion is disputed by monetary economists who contend that people act rationally (i.e. think in real prices) with regard to their wealth. Eldar Shafir, Peter A. Diamond, and Amos Tversky (1997) have provided empirical evidence for the existence of the effect and it has been shown to affect behaviour in a variety of experimental and real-world situations. Shafir et al. also state that money illusion influences economic behaviour in three main ways: Price stickiness. Money illusion has been proposed as one reason why


id: multiple-discovery-20260505-0
file: data/en.wikipedia.org/wiki/Multiple_discovery-0.md
category: reference
title: Multiple discovery
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Multiple_discovery
date_saved: 2026-05-05T09:58:11.447609+00:00
instance: kb-cron
parent: multiple-discovery-20260505-0
summary:
The concept of multiple discovery (also known as simultaneous invention) is the hypothesis that most scientific discoveries and inventions are made independently and more or less simultaneously by multiple scientists and inventors. The concept of multiple discovery opposes a traditional view—the "heroic theory" of invention and discovery. Multiple discovery is analogous to convergent evolution in biological evolution. == Multiples == When Nobel laureates are announced annually—especially in physics, chemistry, physiology, medicine, and economics—increasingly, in the given field, rather than just a single laureate, there are two, or the maximally permissible three, who often have independently made the same discovery. Historians and sociologists have remarked the occurrence, in science, of "multiple independent discovery". Robert K. Merton defined such "multiples" as instances in which similar discoveries are made by scientists working independently of each other. Merton contrasted a "multiple" with a "singleton"—a discovery that has been made uniquely by a single scientist or group of scientists working together. As Merton said, "Sometimes the discoveries are simultaneous or almost so; sometimes a scientist will make a new discovery which, unknown to him, somebody else has made years before." Commonly cited examples of multiple independent discovery are the 17th-century independent formulation of calculus by


id: multiple-discovery-20260505-1
file: data/en.wikipedia.org/wiki/Multiple_discovery-1.md
category: reference
title: Multiple discovery
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Multiple_discovery
date_saved: 2026-05-05T09:58:11.447609+00:00
instance: kb-cron
parent: multiple-discovery-20260505-0
summary:
== Civility == After Isaac Newton and Gottfried Wilhelm Leibniz had exchanged information on their respective systems of calculus in the 1670s, Newton in the first edition of his Principia (1687), in a scholium, apparently accepted Leibniz's independent discovery of calculus. In 1699, however, a Swiss mathematician suggested to Britain's Royal Society that Leibniz had borrowed his calculus from Newton. In 1705 Leibniz, in an anonymous review of Newton's Opticks, implied that Newton's fluxions (Newton's term for differential calculus) were an adaptation of Leibniz's calculus. In 1712 the Royal Society appointed a committee to examine the documents in question; the same year, the Society published a report, written by Newton himself, asserting his priority. Soon after Leibniz died in 1716, Newton denied that his own 1687 Principia scholium "allowed [Leibniz] the invention of the calculus differentialis independently of my own"; and the third edition of Newton's Principia (1726) omitted the tell-tale scholium. It is now accepted that Newton and Leibniz discovered calculus independently of each other. In another classic case of multiple discovery, the two discoverers showed more civility. By June 1858 Charles Darwin had completed over two-thirds of his On the Origin of Species when he received a startling


id: neuroheuristics-20260505-0
file: data/en.wikipedia.org/wiki/Neuroheuristics-0.md
category: reference
title: Neuroheuristics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neuroheuristics
date_saved: 2026-05-05T09:58:12.597579+00:00
instance: kb-cron
parent: neuroheuristics-20260505-0
summary:
Neuroheuristics (or neuristics) studies the dynamic relations within neuroscientific knowledge, using a transdisciplinary studies approach. It was proposed by Alessandro Villa in 2000. == Etymology == The word comes from the Greek νεύρον (neuron, which refers to the nerve cell) and εύρισκω ("euriskein", heuristic, which refers to problem-solving procedures characterized by informal, intuitive and speculative features). == Paradigm == Neuroheuristics defines a scientific paradigm aimed to develop strategies that can be enabled to understand brain and mind following subsequent problems emerging from transdisciplinary studies including philosophy, psychology, neuroscience, pharmacology, physics, artificial intelligence, engineering, computer science, economics and mathematics. The research framework introduced by the neuroheuristic paradigm appears as an essential step for the investigation of the information processing effected by the brain because it is the outcome of nature and nurture, at the crossing of top-down and bottom-up design. Neurobiologists apply a bottom-up research strategy in their studies. This strategy has been able to describe a simple organism's nervous system, such as Caenorhabditis elegans. However, it would be impossible to simultaneously examine all neurons and all variables. This limits the value experimentation using this method could provide. The top-down strategy with the assistance of black box theory appears easier to


id: nicolausian-discounting-20260505-0
file: data/en.wikipedia.org/wiki/Nicolausian_discounting-0.md
category: reference
title: Nicolausian discounting
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Nicolausian_discounting
date_saved: 2026-05-05T09:58:13.887222+00:00
instance: kb-cron
parent: nicolausian-discounting-20260505-0
summary:
Nicolausian discounting is a heuristic technique meant to simplify decision-making involving very small probabilities by ignoring them. The term was coined by philosopher Bradley Monton in a 2019 paper. He defined it this way: "For decision-making, small probabilities should be discounted down to zero before maximizing expected utility." Monton named the concept after Nicolaus I Bernoulli, who suggested it as a solution to his St. Petersburg paradox. Monton translates Bernoulli as writing in 1714 that "cases that have a very small probability must be neglected and assumed to be zero." The term has gained some currency and been mentioned in other writings in philosophy. == Notes == == References ==


id: null-move-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Null-move_heuristic-0.md
category: reference
title: Null-move heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Null-move_heuristic
date_saved: 2026-05-05T09:58:15.058839+00:00
instance: kb-cron
parent: null-move-heuristic-20260505-0
summary:
In computer chess programs, the null-move heuristic is a heuristic technique used to enhance the speed of the alpha–beta pruning algorithm. == Rationale == Alpha–beta pruning speeds the minimax algorithm by identifying cutoffs, points in the game tree where the current position is so good for the side to move that best play by the other side would have avoided it. Since such positions could not have resulted from best play, they and all branches of the game tree stemming from them can be ignored. The faster the program produces cutoffs, the faster the search runs. The null-move heuristic is designed to guess cutoffs with less effort than would otherwise be required, whilst retaining a reasonable level of accuracy. The null-move heuristic is based on the fact that most reasonable chess moves improve the position for the side that played them. So, if the player whose turn it is to move can forfeit the right to move (or make a null move – an illegal action in chess) and still have a position strong enough to produce a cutoff, then the current position would almost certainly produce a cutoff if the current player actually moved. == Implementation == In employing


id: occam-s-razor-20260505-0
file: data/en.wikipedia.org/wiki/Occam's_razor-0.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
In philosophy, Occam's razor (also spelled Ockham's razor or Ocham's razor; Latin: novacula Occami) is the problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements. It is also known as the principle of parsimony or the law of parsimony (Latin: lex parsimoniae). Attributed to William of Ockham, a 14th-century English philosopher and theologian, it is frequently cited as Entia non sunt multiplicanda praeter necessitatem, which translates as "Entities must not be multiplied beyond necessity", although Occam never used those exact words. Popularly, the principle is sometimes paraphrased as "of two competing theories, the simpler explanation of an entity is to be preferred". This philosophical razor advocates that when presented with competing hypotheses about the same prediction and both hypotheses have equal explanatory power, one should prefer the hypothesis that requires the fewest assumptions, and that this is not meant to be a way of choosing between hypotheses that make different predictions. Similarly, in science, Occam's razor is used as an abductive heuristic in the development of theoretical models rather than as a rigorous arbiter between candidate models. == History == The phrase Occam's razor did not appear until a few centuries after William of


id: occam-s-razor-20260505-1
file: data/en.wikipedia.org/wiki/Occam's_razor-1.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
=== Later formulations === To quote Isaac Newton, "We are to admit no more causes of natural things than such as are both true and sufficient to explain their appearances. Therefore, to the same natural effects we must, as far as possible, assign the same causes." In the sentence hypotheses non fingo ("I contrive no hypotheses"), Newton affirms the success of this approach. Bertrand Russell offers a particular version of Occam's razor: "Whenever possible, substitute constructions out of known entities for inferences to unknown entities." Around 1960, Ray Solomonoff founded the theory of universal inductive inference, the theory of prediction based on observations – for example, predicting the next symbol based upon a given series of symbols. The only assumption is that the environment follows some unknown but computable probability distribution. This theory is a mathematical formalization of Occam's razor. Another technical approach to Occam's razor is ontological parsimony. Parsimony means spareness and is also referred to as the Rule of Simplicity. This is considered a strong version of Occam's razor. A variation used in medicine is called the "Zebra": a physician should reject an exotic medical diagnosis when a more commonplace explanation is more likely, derived from Theodore Woodward's


id: occam-s-razor-20260505-2
file: data/en.wikipedia.org/wiki/Occam's_razor-2.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
One justification of Occam's razor is a direct result of basic probability theory. By definition, all assumptions introduce possibilities for error; if an assumption does not improve the accuracy of a theory, its only effect is to increase the probability that the overall theory is wrong. There have also been other attempts to derive Occam's razor from probability theory, including notable attempts made by Harold Jeffreys and E. T. Jaynes. The probabilistic (Bayesian) basis for Occam's razor is elaborated by David J. C. MacKay in chapter 28 of his book Information Theory, Inference, and Learning Algorithms, where he emphasizes that a prior bias in favor of simpler models is not required. William H. Jefferys and James O. Berger (1991) generalize and quantify the original formulation's "assumptions" concept as the degree to which a proposition is unnecessarily accommodating to possible observable data. They state, "A hypothesis with fewer adjustable parameters will automatically have an enhanced posterior probability, due to the fact that the predictions it makes are sharp." The use of "sharp" here is not only a tongue-in-cheek reference to the idea of a razor, but also indicates that such predictions are more accurate than competing predictions. The model they propose


id: occam-s-razor-20260505-3
file: data/en.wikipedia.org/wiki/Occam's_razor-3.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
In science, Occam's razor is used as a heuristic to guide scientists in developing theoretical models rather than as an arbiter between published models. In physics, parsimony was an important heuristic in the development and application of the principle of least action by Pierre Louis Maupertuis and Leonhard Euler, in Albert Einstein's formulation of special relativity, and in the development of quantum mechanics by Max Planck, Werner Heisenberg and Louis de Broglie. In chemistry, Occam's razor is often an important heuristic when developing a model of a reaction mechanism. Although it is useful as a heuristic in developing models of reaction mechanisms, it has been shown to fail as a criterion for selecting among some selected published models. In this context, Einstein himself expressed caution when he formulated Einstein's Constraint: "It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience." An often-quoted version of this constraint (which cannot be verified as posited by Einstein himself) reduces this to "Everything should be kept as simple as possible, but not simpler." In the


id: occam-s-razor-20260505-4
file: data/en.wikipedia.org/wiki/Occam's_razor-4.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
Biologists or philosophers of biology use Occam's razor in either of two contexts both in evolutionary biology: the units of selection controversy and systematics. George C. Williams in his book Adaptation and Natural Selection (1966) argues that the best way to explain altruism among animals is based on low-level (i.e., individual) selection as opposed to high-level group selection. Altruism is defined by some evolutionary biologists (e.g., R. Alexander, 1987; W. D. Hamilton, 1964) as behavior that is beneficial to others (or to the group) at a cost to the individual, and many posit individual selection as the mechanism that explains altruism solely in terms of the behaviors of individual organisms acting in their own self-interest (or in the interest of their genes, via kin selection). Williams was arguing against the perspective of others who propose selection at the level of the group as an evolutionary mechanism that selects for altruistic traits (e.g., D. S. Wilson & E. O. Wilson, 2007). The basis for Williams's contention is that of the two, individual selection is the more parsimonious theory. In doing so he is invoking a variant of Occam's razor known as Morgan's Canon: "In no case is an animal activity to


id: occam-s-razor-20260505-5
file: data/en.wikipedia.org/wiki/Occam's_razor-5.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
=== Religion === In the philosophy of religion, Occam's razor is sometimes applied to the existence of God. William of Ockham himself was a Christian. He believed in God, and in the authority of Christian scripture; he writes that "nothing ought to be posited without a reason given, unless it is self-evident (literally, known through itself) or known by experience or proved by the authority of Sacred Scripture." Ockham believed that an explanation has no sufficient basis in reality when it does not harmonize with reason, experience, or the Bible. Unlike many theologians of his time, though, Ockham did not believe God could be logically proven with arguments. To Ockham, science was a matter of discovery; theology was a matter of revelation and faith. He states: "Only faith gives us access to theological truths. The ways of God are not open to reason, for God has freely chosen to create a world and establish a way of salvation within it apart from any necessary laws that human logic or rationality can uncover." Thomas Aquinas, in the Summa Theologica, uses a formulation of Occam's razor to construct an objection to the idea that God exists, which he refutes directly with a


id: occam-s-razor-20260505-6
file: data/en.wikipedia.org/wiki/Occam's_razor-6.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
=== Penal ethics === In penal theory and the philosophy of punishment, parsimony refers specifically to taking care in the distribution of punishment in order to avoid excessive punishment. In the utilitarian approach to the philosophy of punishment, Jeremy Bentham's "parsimony principle" states that any punishment greater than is required to achieve its end is unjust. The concept is related but not identical to the legal concept of proportionality. Parsimony is a key consideration of the modern restorative justice, and is a component of utilitarian approaches to punishment, as well as the prison abolition movement. Bentham believed that true parsimony would require punishment to be individualised to take account of the sensibility of the individual – an individual more sensitive to punishment should be given a proportionately lesser one, since otherwise needless pain would be inflicted. Later utilitarian writers have tended to abandon this idea, in large part due to the impracticality of determining each alleged criminal's relative sensitivity to specific punishments. === Probability theory and statistics === Marcus Hutter's universal artificial intelligence builds upon Solomonoff's mathematical formalization of the razor to calculate the expected value of an action. There are various papers in scholarly journals deriving formal versions of


id: occam-s-razor-20260505-7
file: data/en.wikipedia.org/wiki/Occam's_razor-7.md
category: reference
title: Occam's razor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Occam's_razor
date_saved: 2026-05-05T09:58:16.211237+00:00
instance: kb-cron
parent: occam-s-razor-20260505-0
summary:
=== Software development === In software development, the rule of least power argues the correct programming language to use is the one that is simplest while also solving the targeted software problem. In that form the rule is often credited to Tim Berners-Lee since it appeared in his design guidelines for the original Hypertext Transfer Protocol. Complexity in this context is measured either by placing a language into the Chomsky hierarchy or by listing idiomatic features of the language and comparing according to some agreed to scale of difficulties between idioms. Many languages once thought to be of lower complexity have evolved or later been discovered to be more complex than originally intended; so, in practice this rule is applied to the relative ease of a programmer to obtain the power of the language, rather than the precise theoretical limits of the language. === Artificial intelligence === Scientists have discovered that deep neural networks (DNN) prefer simpler mathematical functions while learning. This simplicity bias enables DNNs to overcome overfitting – a scenario where the model gets overwhelmed with noise due to the presence of too many parameters. == Controversial aspects == Occam's razor is not an embargo against the positing


id: parallel-tempering-20260505-0
file: data/en.wikipedia.org/wiki/Parallel_tempering-0.md
category: reference
title: Parallel tempering
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Parallel_tempering
date_saved: 2026-05-05T09:58:17.377976+00:00
instance: kb-cron
parent: parallel-tempering-20260505-0
summary:
Parallel tempering, in physics and statistics, is a computer simulation method typically used to find the lowest energy state of a system of many interacting particles. It addresses the problem that at high temperatures, one may have a stable state different from low temperature, whereas simulations at low temperatures may become "stuck" in a metastable state. It does this by using the fact that the high temperature simulation may visit states typical of both stable and metastable low temperature states. More specifically, parallel tempering (also known as replica exchange MCMC sampling), is a simulation method aimed at improving the dynamic properties of Monte Carlo method simulations of physical systems, and of Markov chain Monte Carlo (MCMC) sampling methods more generally. The replica exchange method was originally devised by Robert Swendsen and J. S. Wang, then extended by Charles J. Geyer, and later developed further by Giorgio Parisi, Koji Hukushima and Koji Nemoto, and others. Y. Sugita and Y. Okamoto also formulated a molecular dynamics version of parallel tempering; this is usually known as replica-exchange molecular dynamics or REMD. Essentially, one runs N copies of the system, randomly initialized, at different temperatures. Then, based on the Metropolis criterion one exchanges configurations


id: peak-end-rule-20260505-0
file: data/en.wikipedia.org/wiki/Peak–end_rule-0.md
category: reference
title: Peak–end rule
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Peak–end_rule
date_saved: 2026-05-05T09:58:18.581650+00:00
instance: kb-cron
parent: peak-end-rule-20260505-0
summary:
The peak–end rule is a psychological heuristic in which people judge an experience largely based on how they felt at its peak (i.e., its most intense point) and at its end, rather than based on the total sum or average of every moment of the experience. The effect occurs regardless of whether the experience is pleasant or unpleasant. To the heuristic, other information aside from that of the peak and end of the experience is not lost, but it is not used. This includes net pleasantness or unpleasantness and how long the experience lasted. The peak–end rule is thereby a specific form of the more general extension neglect and duration neglect. == Overview == The peak–end rule is an elaboration on the snapshot model of remembered utility proposed by Barbara Fredrickson and Daniel Kahneman. This model dictates that an event is not judged by the entirety of an experience, but by prototypical moments (or snapshots) as a result of the representativeness heuristic. The remembered value of snapshots dominates the actual value of an experience. Fredrickson and Kahneman theorized that these snapshots are actually the average of the most affectively intense moment of an experience and the feeling experienced at the


id: peak-end-rule-20260505-1
file: data/en.wikipedia.org/wiki/Peak–end_rule-1.md
category: reference
title: Peak–end rule
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Peak–end_rule
date_saved: 2026-05-05T09:58:18.581650+00:00
instance: kb-cron
parent: peak-end-rule-20260505-0
summary:
=== Recency bias in memory (i.e., why the end is memorable) === People exhibit serial position effects such that they have better memory for both the beginning and end of sequences, phenomena known as primacy bias and recency bias, respectively. A paper by Garbinsky, Morewedge, and Shiv (2014) found evidence that for extended hedonic experiences, better memory for the end of the experience than the beginning (recency > primacy) can be attributed to memory interference effects. As a person eats potato chips, for example, the formation of a new memory of the most recently eaten chip makes it harder for them to recall how the previously eaten chips tasted. Garbinsky and colleagues found that (1) recency effects better predicted recalled enjoyment of a small meal (e.g., eating 5 or 15 chips) than did primacy effects, (2) that people had a worse memory for the first bite of the meal than the last bite of the meal, but (3) providing people with their ratings of the first bite lead them to use their enjoyment of that first bite as much as their enjoyment of the last bite when rating their overall enjoyment of the meal. == Applications == === Business ===


id: peak-end-rule-20260505-2
file: data/en.wikipedia.org/wiki/Peak–end_rule-2.md
category: reference
title: Peak–end rule
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Peak–end_rule
date_saved: 2026-05-05T09:58:18.581650+00:00
instance: kb-cron
parent: peak-end-rule-20260505-0
summary:
=== Medical procedures === The peak–end rule is particularly salient in regard to medical procedures, since it suggests that it is preferable to have longer procedures that include a period of decreased discomfort than to have shorter procedures. In particular, the rule "suggests that the memory of a painful medical treatment is likely to be less aversive if relief from the pain is gradual than if relief is abrupt". Furthermore, the quality of a remembered procedure can drastically influence medical futures. If people recall necessary but onerous procedures more positively, then they are more likely to return for repeat procedures later in life. However, factoring the effect of the peak–end rule upon evaluations of medical procedures is problematic, since adding a period of decreasing pain to a procedure is still added pain. Even though this certainly yields a better memory of the process, the patient still endures more pain than is strictly necessary. Doctors and patients are forced to confront the choice between objectively less painful forms of treatment and forms of treatment that will be remembered more favorably. Kahneman claims that "it is safe to assume that few patients will agree to expose themselves to pain for the sole


id: pollen-calendar-20260505-0
file: data/en.wikipedia.org/wiki/Pollen_calendar-0.md
category: reference
title: Pollen calendar
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Pollen_calendar
date_saved: 2026-05-05T09:58:19.787742+00:00
instance: kb-cron
parent: pollen-calendar-20260505-0
summary:
A pollen calendar is used to show the peak pollen times for different types of plant pollen, which causes allergic reactions in certain people. == In forensics == A pollen calendar can be a very useful tool in forensic science, because it can be used to place the month, or week, or date of death. The use of pollen for criminal investigation purposes is called "forensic palynology". However, the use of a pollen calendar to set the date of death should be used with extreme caution, and only by a carefully trained expert witness. The CSI effect has put pressure on some police officers and district attorneys to provide pollen-based evidence, but such evidence "appear[s] to be of limited use in the forensic context where outcomes are scrutinised in court." == See also == Aeroallergen National Pollen and Aerobiology Research Unit Hay fever == References == == External links == United States pollen calendars (Does not lead to any pollen calendars) Pollen calendar for the UK created by the National Pollen and Aerobiology Research Unit at the University of Worcester New Zealand allergy pages and New Zealand pollen calendar (printable PDF) Australian pollen calendar (printable PDF)


id: principle-of-least-astonishment-20260505-0
file: data/en.wikipedia.org/wiki/Principle_of_least_astonishment-0.md
category: reference
title: Principle of least astonishment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Principle_of_least_astonishment
date_saved: 2026-05-05T09:58:20.938491+00:00
instance: kb-cron
parent: principle-of-least-astonishment-20260505-0
summary:
In user interface design and software design, the principle of least astonishment (POLA), also known as principle of least surprise (POLS), proposes that a component of a system should behave in a way that most users will expect it to behave, and therefore not astonish or surprise users. The following is a corollary of the principle: "If a necessary feature has a high astonishment factor, it may be necessary to redesign the feature." The principle has been in use in relation to computer interaction since at least the 1970s. Although first formalized in the field of computer technology, the principle can be applied broadly in other fields. For example, in writing, a cross-reference to another part of the work or a hyperlink should be phrased in a way that accurately tells the reader what to expect. == Origin == An early reference to the "Law of Least Astonishment" appeared in the PL/I Bulletin in 1967 (PL/I is a programming language released by IBM in 1966). By the late 1960s, PL/I had become infamous for violating the law, for example because, due to PL/I's precision conversion rules, the expressions 25 + 1/3 and 1/3 + 25 would either produce a fatal


id: priority-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Priority_heuristic-0.md
category: reference
title: Priority heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Priority_heuristic
date_saved: 2026-05-05T09:58:22.097689+00:00
instance: kb-cron
parent: priority-heuristic-20260505-0
summary:
The priority heuristic is a simple, lexicographic decision strategy that helps decide for a good option. == Psychology == In psychology, priority heuristics correctly predict classic violations of expected utility theory such as the Allais paradox, the four-fold pattern, the certainty effect, the possibility effect, or intransitivities. The heuristic maps onto Rubinstein’s three-step model, according to which people first check dominance and stop if it is present, otherwise they check for dissimilarity. To highlight Rubinstein’s model consider the following choice problem: Dominance is absent, and while chances are similar monetary outcomes are not. Rubinstein’s model predicts that people check for dissimilarity and consequently choose Gamble I. Unfortunately, dissimilarity checks are often not decisive, and Rubinstein suggested that people proceed to a third step that he left unspecified. The priority heuristic elaborates on Rubinstein’s framework by specifying this Step 3. === Priority heuristic === For illustrative purposes consider a choice between two simple gambles of the type “a chance c of winning monetary amount x; a chance (100 - c) of winning amount y.” A choice between two such gambles contain four reasons for choosing: the maximum gain, the minimum gain, and their respective chances; because chances are complementary, three reasons


id: the-purpose-of-a-system-is-what-it-does-20260505-0
file: data/en.wikipedia.org/wiki/The_purpose_of_a_system_is_what_it_does-0.md
category: reference
title: The purpose of a system is what it does
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/The_purpose_of_a_system_is_what_it_does
date_saved: 2026-05-05T09:58:23.292222+00:00
instance: kb-cron
parent: the-purpose-of-a-system-is-what-it-does-20260505-0
summary:
The purpose of a system is what it does (POSIWID) is a heuristic in systems thinking coined by the British management consultant Stafford Beer, who stated that there is "no point in claiming that the purpose of a system is to do what it constantly fails to do". It is widely used by systems theorists, and is generally invoked to counter the notion that the purpose of a system can be read from the intentions of those who design, operate or promote it. When a system's side effects or unintended consequences reveal that its behaviour is poorly understood, then the POSIWID perspective can balance political understandings of system behaviour with a more straightforwardly descriptive view. == Origins == Beer used the phrase in his 1979 book The Heart of Enterprise, and subsequently many times in public addresses. Speaking to the University of Valladolid in October 2001, he said: According to the cybernetician, the purpose of a system is what it does. This is a basic dictum. It stands for bald fact, which makes a better starting point in seeking understanding than the familiar attributions of good intention, prejudices about expectations, moral judgement, or sheer ignorance of circumstances. == Uses ==


id: recognition-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Recognition_heuristic-0.md
category: reference
title: Recognition heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Recognition_heuristic
date_saved: 2026-05-05T09:58:24.478211+00:00
instance: kb-cron
parent: recognition-heuristic-20260505-0
summary:
The recognition heuristic, originally termed the recognition principle, has been used as a model in the psychology of judgment and decision making and as a heuristic in artificial intelligence. The goal is to make inferences about a criterion that is not directly accessible to the decision maker, based on recognition retrieved from memory. This is possible if recognition of alternatives has relevance to the criterion. For two alternatives, the heuristic is defined as: If one of two objects is recognized and the other is not, then infer that the recognized object has the higher value with respect to the criterion. The recognition heuristic is part of the "adaptive toolbox" of "fast and frugal" heuristics proposed by Gigerenzer and Goldstein. It is one of the most frugal of these, meaning it is simple or economical. In their original experiment, Daniel Goldstein and Gerd Gigerenzer quizzed students in Germany and the United States on the populations of both German and American cities. Participants received pairs of city names and had to indicate which city has more inhabitants. In this and similar experiments, the recognition heuristic typically describes about 80–90% of participants' choices, in cases where they recognize one but not the other


id: recognition-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Recognition_heuristic-1.md
category: reference
title: Recognition heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Recognition_heuristic
date_saved: 2026-05-05T09:58:24.478211+00:00
instance: kb-cron
parent: recognition-heuristic-20260505-0
summary:
== Neuropsychological evidence == The recognition heuristic can also be depicted using neuroimaging techniques. A number of studies have shown that people do not automatically use the recognition heuristic when it can be applied, but evaluate its ecological validity. It is less clear, however, how this evaluation process can be modeled. A functional magnetic resonance imaging study tested whether the two processes, recognition and evaluation, can be separated on a neural basis. Participants were given two tasks; the first involved only a recognition judgment ("Have you ever heard of Modena? Milan?"), while the second involved an inference in which participants could rely on the recognition heuristic ("Which city has the larger population: Milan or Modena?"). For mere recognition judgments, activation in the precuneus, an area that is known from independent studies to respond to recognition confidence, was reported. In the inference task, precuneus activation was also observed, as predicted, and activation was detected in the anterior frontomedian cortex (aFMC), which has been linked in earlier studies to evaluative judgments and self-referential processing. The aFMC activation could represent the neural basis of this evaluation of ecological rationality. Some researchers have used event-related potentials (ERP) to test psychological mechanisms behind the recognition


id: representativeness-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Representativeness_heuristic-0.md
category: reference
title: Representativeness heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Representativeness_heuristic
date_saved: 2026-05-05T09:58:25.644416+00:00
instance: kb-cron
parent: representativeness-heuristic-20260505-0
summary:
The representativeness heuristic is used when making judgments about the probability of an event being representational in character and essence of a known prototypical event. It is one of a group of heuristics (simple rules governing judgment or decision-making) proposed by psychologists Amos Tversky and Daniel Kahneman in the early 1970s as "the degree to which [an event] (i) is similar in essential characteristics to its parent population, and (ii) reflects the salient features of the process by which it is generated". The representativeness heuristic works by comparing an event to a prototype or stereotype that we already have in mind. For example, if we see a person who is dressed in eccentric clothes and reading a poetry book, we might be more likely to think that they are a poet than an accountant. This is because the person's appearance and behavior are more representative of the stereotype of a poet than an accountant. The representativeness heuristic can be a useful shortcut in some cases, but it can also lead to errors in judgment. For example, if we only see a small sample of people from a particular group, we might overestimate the degree to which they are representative of


id: representativeness-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Representativeness_heuristic-1.md
category: reference
title: Representativeness heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Representativeness_heuristic
date_saved: 2026-05-05T09:58:25.644416+00:00
instance: kb-cron
parent: representativeness-heuristic-20260505-0
summary:
"Base-rate group", who were given the instructions: "Consider all the first-year graduate students in the U.S. today. Please write down your best guesses about the percentage of students who are now enrolled in the following nine fields of specialization." The nine fields given were business administration, computer science, engineering, humanities and education, law, library science, medicine, physical and life sciences, and social science and social work. "Similarity group", who were given a personality sketch. "Tom W. is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and by flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to feel little sympathy for other people and does not enjoy interacting with others. Self-centered, he nonetheless has a deep moral sense." The participants in this group were asked to rank the nine areas listed in part 1 in terms of how similar Tom W. is to the prototypical graduate student of each area. "Prediction group", who were given the personality sketch


id: representativeness-heuristic-20260505-2
file: data/en.wikipedia.org/wiki/Representativeness_heuristic-2.md
category: reference
title: Representativeness heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Representativeness_heuristic
date_saved: 2026-05-05T09:58:25.644416+00:00
instance: kb-cron
parent: representativeness-heuristic-20260505-0
summary:
As can be seen, the base rate P(H) is ignored in this equation, leading to the base rate fallacy. A base rate is a phenomenon's basic rate of incidence. The base rate fallacy describes how people do not take the base rate of an event into account when solving probability problems. This was explicitly tested by Dawes, Mirels, Gold and Donahue (1993) who had people judge both the base rate of people who had a particular personality trait and the probability that a person who had a given personality trait had another one. For example, participants were asked how many people out of 100 answered true to the question "I am a conscientious person" and also, given that a person answered true to this question, how many would answer true to a different personality question. They found that participants equated inverse probabilities (e.g., P ( c o n s c i e n t i o u s | n e u r o t i c ) = P ( n e u r o t i c | c o n s c i e n t i o u s ) {\displaystyle P(conscientious|neurotic)=P(neurotic|conscientious)} ) even when it


id: representativeness-heuristic-20260505-3
file: data/en.wikipedia.org/wiki/Representativeness_heuristic-3.md
category: reference
title: Representativeness heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Representativeness_heuristic
date_saved: 2026-05-05T09:58:25.644416+00:00
instance: kb-cron
parent: representativeness-heuristic-20260505-0
summary:
=== Disjunction fallacy === From probability theory the disjunction of two events is at least as likely as either of the events individually. For example, the probability of being either a physics or biology major is at least as likely as being a physics major, if not more likely. However, when a personality description (data) seems to be very representative of a physics major (e.g., having a pocket protector) over a biology major, people judge that it is more likely for this person to be a physics major than a natural sciences major (which is a superset of physics). Evidence that the representativeness heuristic may cause the disjunction fallacy comes from Bar-Hillel and Neter (1993). They found that people judge a person who is highly representative of being a statistics major (e.g., highly intelligent, does math competitions) as being more likely to be a statistics major than a social sciences major (superset of statistics), but they do not think that he is more likely to be a Hebrew language major than a humanities major (superset of Hebrew language). Thus, only when the person seems highly representative of a category is that category judged as more probable than its superordinate category.


id: reversal-test-20260505-0
file: data/en.wikipedia.org/wiki/Reversal_test-0.md
category: reference
title: Reversal test
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reversal_test
date_saved: 2026-05-05T09:58:26.858290+00:00
instance: kb-cron
parent: reversal-test-20260505-0
summary:
The reversal test is a heuristic designed to spot and eliminate status quo bias, an emotional bias irrationally favouring the current state of affairs. The test is applicable to the evaluation of any decision involving a potential deviation from the status quo along some continuous dimension. The reversal test was introduced in the context of the bioethics of human enhancement by Nick Bostrom and Toby Ord. == Concept == Bostrom and Ord introduced the reversal test to provide an answer to the question of how one can, given that humans might suffer from irrational status quo bias, distinguish between valid criticisms of a proposed increase in some human trait and criticisms merely motivated by resistance to change. The reversal test attempts to do this by asking whether it would be a good thing if the trait was decreased: An example given is that if someone objects that an increase in intelligence would be a bad thing due to more dangerous weapons being made etc., the objector to that position would then ask "Shouldn't we decrease intelligence then?" "Reversal Test: When a proposal to change a certain parameter is thought to have bad overall consequences, consider a change to the same


id: reverse-logistics-network-modelling-20260505-0
file: data/en.wikipedia.org/wiki/Reverse_logistics_network_modelling-0.md
category: reference
title: Reverse logistics network modelling
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reverse_logistics_network_modelling
date_saved: 2026-05-05T09:58:28.013867+00:00
instance: kb-cron
parent: reverse-logistics-network-modelling-20260505-0
summary:
Reverse logistics is for all operations related to the reuse of products and materials. It is "the process of moving goods from their typical final destination for the purpose of capturing value, or proper disposal. Remanufacturing and refurbishing activities also may be included in the definition of reverse logistics." In order to model reverse logistics network from an economics point of view, the following simplified reverse logistics system has to be set. In this model, the products are gathered from the consumers and transferred back to the producers, hence the direction of the flow in the distribution supply chain is reversed, and the model is expanded with the recovery centre. First of all, the used products are collected from the consumers and moved to the recovery centre, where the condition of the products are examined according to their end of life cycle. If there is still recapture value, then the product is disassembled as preparation for further reprocessing, which means physical transformation to new customer. Otherwise, the used product is disposed and transferred to the landfill site. According to the introduced model the main differences between forward and reverse logistics can be identified: Uncertainty on the quantity, quality and timing


id: rippling-20260505-0
file: data/en.wikipedia.org/wiki/Rippling-0.md
category: reference
title: Rippling
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rippling
date_saved: 2026-05-05T09:58:29.200961+00:00
instance: kb-cron
parent: rippling-20260505-0
summary:
In computer science, more particularly in automated theorem proving, rippling is a group of meta-level heuristics, developed primarily in the Mathematical Reasoning Group in the School of Informatics at the University of Edinburgh, and most commonly used to guide inductive proofs in automated theorem proving systems. Rippling may be viewed as a restricted form of rewrite system, where special object level annotations are used to ensure fertilization upon the completion of rewriting, with a measure decreasing requirement ensuring termination for any set of rewrite rules and expression. == History == Raymond Aubin was the first person to use the term "rippling out" whilst working on his 1976 PhD thesis at the University of Edinburgh. He recognised a common pattern of movement during the rewriting stage of inductive proofs. Alan Bundy later turned this concept on its head by defining rippling to be this pattern of movement, rather than a side effect. Since then, "rippling sideways", "rippling in" and "rippling past" were coined, so the term was generalised to rippling. Rippling continues to be developed at Edinburgh, and elsewhere, as of 2007. Rippling has been applied to many problems traditionally viewed as being hard in the inductive theorem proving community, including


id: rosy-retrospection-20260505-0
file: data/en.wikipedia.org/wiki/Rosy_retrospection-0.md
category: reference
title: Rosy retrospection
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosy_retrospection
date_saved: 2026-05-05T09:58:30.436035+00:00
instance: kb-cron
parent: rosy-retrospection-20260505-0
summary:
Rosy retrospection is a proposed psychological phenomenon of recalling the past more positively than it was actually experienced. The highly unreliable nature of human memory is well documented and accepted amongst psychologists. Some research suggests a 'blue retrospective' which also exaggerates negative emotions, creating a bipolar distortion of affective memory that depends on personality, time, and developmental stage. Though it is a cognitive bias which distorts one's view of reality, it is suggested that rosy retrospection serves a useful purpose in increasing self-esteem and sense of well-being. Simplifications and exaggerations of memories that occur in rosy retrospection may make it easier for the brain to store long-term memories, as removing details may reduce the burden of those memories by requiring the generation and maintenance of fewer neural connections. In evolutionary terms, such bias may have persisted because it encourages repeated engagement in adaptive behaviors, such as social bonding, exploration, and caregiving, even when those experiences were mixed or mildly unpleasant at the time. This cognitive efficiency allows the brain to preserve core meaningful experiences without being overwhelmed by trivial or distressing details. Rosy retrospection is closely related to nostalgia, but differs in that it specifically involves perceiving the past as


id: rosy-retrospection-20260505-1
file: data/en.wikipedia.org/wiki/Rosy_retrospection-1.md
category: reference
title: Rosy retrospection
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosy_retrospection
date_saved: 2026-05-05T09:58:30.436035+00:00
instance: kb-cron
parent: rosy-retrospection-20260505-0
summary:
=== Exaggeration of both negative and positive emotions === Some studies have found evidence of a bias to exaggerating negative emotions - a.k.a. a 'blue' retrospective - as well as positive ones. These results run counter to the assumption that memory distortion is universally positive and suggest that it is flexible and that memory distortion is a response to individual differences and circumstances. A 2016 study of 179 adults tracked their emotional state at regular intervals over 10 days, upon reflection after one day, and again after 1-2 months. It found that for both positive and negative emotions, stronger peak emotions (the strongest rating of the day) were more likely to result in exaggerated recollections upon reflection. Unlike the study above, it did not find that this effect increased with time. It also found a negative correlation with the average rating and the exaggerated recollections; suggesting those who consistently experienced stronger emotion recall more accurately. Additionally, it found extraverted personalities were more likely to have ‘rosy’ positive bias whereas neurotic personalities were more likely to have negative 'blue' bias on recall. This coincides with wider personality studies suggesting that extraversion facilitates positive emotional processing, and neuroticism increases sensitivity towards negative


id: rosy-retrospection-20260505-2
file: data/en.wikipedia.org/wiki/Rosy_retrospection-2.md
category: reference
title: Rosy retrospection
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosy_retrospection
date_saved: 2026-05-05T09:58:30.436035+00:00
instance: kb-cron
parent: rosy-retrospection-20260505-0
summary:
=== Limitations === Relying on subjective ratings, the above studies could suffer from demand characteristics: participants may guess the study's goals and expected results, unconsciously changing their answers thinking they are 'supposed' to recall their emotions inaccurately. Experiments may lack ecological validity. These studies may be vulnerable to sample biases. They rely on small samples which are more likely to be unrepresentative of the general population by unlucky chance. Many of the samples are homogenous to varying extents, with subjects often being relatively young, in education, and western. A similar sample bias may occur in the way researchers find subjects. Potentially those who come across and are appealed to join and remain in studies will be those with relatively more free-time, better education, higher wealth and income, etc. Though the studies took varying efforts to reduce this by ensuring a balance of ages, ethnicities, sexes, etc. While the studies attempted to balance it on different levels (age, ethnic group, sex, etc.), it is less researched cross-culturally or by socioeconomic stratification. These studies typically asked subjects to recall their emotions only days or weeks after an event. Thus they may predict little for rosy retrospection on the scale of months, years,


id: satisficing-20260505-0
file: data/en.wikipedia.org/wiki/Satisficing-0.md
category: reference
title: Satisficing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Satisficing
date_saved: 2026-05-05T09:58:31.658331+00:00
instance: kb-cron
parent: satisficing-20260505-0
summary:
Satisficing is a decision-making strategy or cognitive heuristic that entails searching through the available alternatives until an acceptability threshold is met, without necessarily maximizing any specific objective. The term satisficing, a portmanteau of satisfy and suffice, was introduced by Herbert A. Simon in 1956, although the concept was first posited in his 1947 book Administrative Behavior. Simon used satisficing to explain the behavior of decision makers under circumstances in which an optimal solution cannot be determined. He maintained that many natural problems are characterized by computational intractability or a lack of information, both of which preclude the use of mathematical optimization procedures. He observed in his Nobel Prize in Economics speech that "decision makers can satisfice either by finding optimum solutions for a simplified world, or by finding satisfactory solutions for a more realistic world. Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science". Simon formulated the concept within a novel approach to rationality, which posits that rational choice theory is an unrealistic description of human decision processes and calls for psychological realism. He referred to this approach as bounded rationality. Moral satisficing is a branch of bounded rationality that


id: satisficing-20260505-1
file: data/en.wikipedia.org/wiki/Satisficing-1.md
category: reference
title: Satisficing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Satisficing
date_saved: 2026-05-05T09:58:31.658331+00:00
instance: kb-cron
parent: satisficing-20260505-0
summary:
=== Optimization === One popular method for rationalizing satisficing is optimization when all costs, including the cost of the optimization calculations themselves and the cost of getting information for use in those calculations, are considered. As a result, the eventual choice is usually sub-optimal in regard to the main goal of the optimization, i.e., different from the optimum in the case that the costs of choosing are not taken into account. ==== As a form of optimization ==== Alternatively, satisficing can be considered to be just constraint satisfaction, the process of finding a solution satisfying a set of constraints, without concern for finding an optimum. Any such satisficing problem can be formulated as an (equivalent) optimization problem using the indicator function of the satisficing requirements as an objective function. More formally, if X denotes the set of all options and S ⊆ X denotes the set of "satisficing" options, then selecting a satisficing solution (an element of S) is equivalent to the following optimization problem max s ∈ X I S ( s ) {\displaystyle \max _{s\in X}I_{S}(s)} where Is denotes the Indicator function of S, that is I S ( s ) := { 1 , s ∈ S


id: satisficing-20260505-2
file: data/en.wikipedia.org/wiki/Satisficing-2.md
category: reference
title: Satisficing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Satisficing
date_saved: 2026-05-05T09:58:31.658331+00:00
instance: kb-cron
parent: satisficing-20260505-0
summary:
=== Endogenous aspiration levels === What determines the aspiration level may be derived from past experience (some function of an agent's or firm's previous payoffs), or some organizational or market institutions. For example, if we think of managerial firms, the managers will be expected to earn normal profits by their shareholders. Other institutions may have specific targets imposed externally (for example state-funded universities in the UK have targets for student recruitment). An economic example is the Dixon model of an economy consisting of many firms operating in different industries, where each industry is a duopoly. The endogenous aspiration level is the average profit in the economy. This represents the power of the financial markets: in the long-run firms need to earn normal profits or they die (as Armen Alchian once said, "This is the criterion by which the economic system selects survivors: those who realize positive profits are the survivors; those who suffer losses disappear"). We can then think what happens over time. If firms are earning profits at or above their aspiration level, then they just stay doing what they are doing (unlike the optimizing firm which would always strive to earn the highest profits possible). However, if the


id: scientific-consensus-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_consensus-0.md
category: reference
title: Scientific consensus
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_consensus
date_saved: 2026-05-05T09:58:32.876488+00:00
instance: kb-cron
parent: scientific-consensus-20260505-0
summary:
Scientific consensus is the collective judgment, position, and opinion of the vast majority of active, qualified experts on a conclusion in a specific scientific discipline. Scientific consensus results from the self-correcting scientific process of peer review, replication of the event through the scientific method, scholarly debate, meta-analysis, and publication of high-quality review articles, monographs, or guidelines in reputable books and journals to establish facts and durable knowledge about the topic. Reaching consensus requires significant scientific agreement among qualified experts, a process based on scientific substantiation of a claim that meets the burden of proof by proposing a possible cause-and-effect mechanism supported by the totality of evidence, leading to agreement among experts. In many countries, scientific consensus established on significant scientific agreement is the basis for regulatory approval of drugs to specify a health claim for the properties of the approved therapeutic agent. Consensus is achieved through scholarly communication at conferences, the publication process, replication of reproducible results by others, debate, and peer review. A conference meant to create a consensus is called a consensus conference. Such measures within a discipline can establish a consensus, although communicating to the lay public that consensus exists may be difficult because the "normal" debates


id: scientific-consensus-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_consensus-1.md
category: reference
title: Scientific consensus
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_consensus
date_saved: 2026-05-05T09:58:32.876488+00:00
instance: kb-cron
parent: scientific-consensus-20260505-0
summary:
There are many philosophical and historical theories as to how scientific consensus changes over time. Because the history of scientific change is extremely complicated, and because there is a tendency to project "winners" and "losers" onto the past in relation to the current scientific consensus, it is very difficult to come up with accurate and rigorous models for scientific change. This is made exceedingly difficult also in part because each of the various branches of science functions in somewhat different ways with different forms of evidence and experimental approaches. Most models of scientific change rely on new data produced by scientific experiment. Karl Popper proposed that since no amount of experiments could ever prove a scientific theory, but a single experiment could disprove one, science should be based on falsification. Whilst this forms a logical theory for science, it is in a sense "timeless" and does not necessarily reflect a view on how science should progress over time. Among the most influential challengers of this approach was Thomas Kuhn, who argued instead that experimental data always provide some data which cannot fit completely into a theory, and that falsification alone did not result in scientific change or an undermining of


id: scientific-enterprise-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_enterprise-0.md
category: reference
title: Scientific enterprise
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_enterprise
date_saved: 2026-05-05T09:58:34.090678+00:00
instance: kb-cron
parent: scientific-enterprise-20260505-0
summary:
A scientific enterprise is a science-based project developed by, or in cooperation with, a private entrepreneur. For example, in the Age of Exploration, leaders like Henry the Navigator founded schools of navigation, from which stemmed voyages of exploration. == Examples of enterprising scientific organizations == Each organization listed below has the ability to conduct scientific research on an extended basis, involving multiple researchers over an extended time. Generally, the research is funded not only for the science itself, but for some application which shows promise for the enterprise. But the researchers, if left to their own choices, will tend to follow their research interest, which is essential for the long-term health of their chosen field. Note that a successful scientific enterprise is not equivalent to a successful high-tech enterprise or to a successful business enterprise, but that they form an ecology, a food chain. The Max Planck Institute, which supports fundamental research in the natural, life and social sciences, the arts and humanities The RAND Corporation, founded as a research corporation. Did groundbreaking work in the field of artificial intelligence The Jet Propulsion Laboratory, founded by Theodore von Kármán Bell Laboratories, renowned for the quality of its scientific work and


id: similarity-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Similarity_heuristic-0.md
category: reference
title: Similarity heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Similarity_heuristic
date_saved: 2026-05-05T09:58:35.270580+00:00
instance: kb-cron
parent: similarity-heuristic-20260505-0
summary:
The similarity heuristic is a psychological heuristic pertaining to how people make judgments based on similarity. More specifically, the similarity heuristic is used to account for how people make judgments based on the similarity between current situations and other situations or prototypes of those situations. At its most basic level, the similarity heuristic is an adaptive strategy. The goal of the similarity heuristic is maximizing productivity through favorable experience while not repeating unfavorable experiences. Decisions based on how favorable or unfavorable the present seems are based on how similar the past was to the current situation. For example, a person may use the similarity heuristic when deciding on a book purchase. If a novel has a plot similar to that of novels read and enjoyed or the author has a writing style similar to that of favored authors, the purchasing decision will be positively influenced. A book with similar characteristics to previously pleasurable books is likely to also be enjoyed, causing the person to decide to obtain it. == Background == The similarity heuristic directly emphasizes learning from past experience. For example, the similarity heuristic has been observed indirectly in experiments such as phonological similarity tests. These tests observe how


id: simulation-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Simulation_heuristic-0.md
category: reference
title: Simulation heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Simulation_heuristic
date_saved: 2026-05-05T09:58:36.449215+00:00
instance: kb-cron
parent: simulation-heuristic-20260505-0
summary:
The simulation heuristic is a psychological heuristic, or simplified mental strategy, according to which people determine the likelihood of an event based on how easy it is to picture the event mentally. Partially as a result, people experience more regret over outcomes that are easier to imagine, such as "near misses". The simulation heuristic was first theorized by psychologists Daniel Kahneman and Amos Tversky as a specialized adaptation of the availability heuristic to explain counterfactual thinking and regret. However, it is not the same as the availability heuristic. Specifically the simulation heuristic is defined as "how perceivers tend to substitute normal antecedent events for exceptional ones in psychologically 'undoing' this specific outcome." Kahneman and Tversky also believed that people used this heuristic to understand and predict other's behavior in certain circumstances and to answer questions involving counterfactual propositions. People, they believe, do this by mentally undoing events that have occurred and then running mental simulations of the events with the corresponding input values of the altered model. For example, a study was proposed that provided a group of participants with a situation describing two men who were delayed by half an hour in a traffic jam on the way to


id: simulation-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Simulation_heuristic-1.md
category: reference
title: Simulation heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Simulation_heuristic
date_saved: 2026-05-05T09:58:36.449215+00:00
instance: kb-cron
parent: simulation-heuristic-20260505-0
summary:
== Applications == This heuristic has shown to be a salient feature of clinical anxiety and its disorders, which are marked by heighted expectations of future negative events. A study done by David Raune and Andrew Macleod tried to tie the cognitive mechanisms that underlie this type of judgment to the simulation heuristic. Their findings showed that anxious patient's simulation heuristic scores were correlated with the subjective probability. Such that, the more reasons anxious patients could think of why negative events would happen, relative to the number why they would not happen, the higher their subjective probability judgment that the events would happen to them. Further it was found that anxious patients displayed increase access to the simulation compared to control patients. They also found support for the hypothesis that the easier it was for anxious patients to form the visual image, the greater the subjective probability that the event would happen to them. Through this work they purposed that the main clinical implication of the simulation heuristic results is that, in order to lower elevated subjective probability in clinical anxiety, patients should be encouraged to think of more reasons why the negative events will not occur then why they


id: smith-s-laws-20260505-0
file: data/en.wikipedia.org/wiki/Smith's_laws-0.md
category: reference
title: Smith's laws
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Smith's_laws
date_saved: 2026-05-05T09:58:37.582177+00:00
instance: kb-cron
parent: smith-s-laws-20260505-0
summary:
In geology, Smith's laws are two rules, formulated by William Smith (1769–1839), which aid in the determination of geological succession. They are fundamental to the production of geological maps. == The laws == Both laws were first published by Smith in Strata Identified by Fossils, 1816–1819. === Smith's first law === Smith's first law is the Principle of Superposition. This states that newer rock beds will lie on top of older rock beds unless the succession has been overturned. Overturning of the beds causes the succession order to be reversed. This can be caused by folding that is so severe that the beds are moved past the perpendicular. Beds can also be put out of order by an overthrust thrust fault (Jackson, p. 128). === Smith's second law === Smith's second law is the Law of Strata identified by fossils. This states that each stratum in the succession contains a distinctive set of fossils. This law allows beds to be identified as belonging to the same stratum even when the horizon between them is not continuous (Jackson, p. 128). == Geological mapping == Smith used these new techniques, together with knowledge he had accumulated as a canal engineer and mineral


id: social-heuristics-20260505-0
file: data/en.wikipedia.org/wiki/Social_heuristics-0.md
category: reference
title: Social heuristics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Social_heuristics
date_saved: 2026-05-05T09:58:38.808102+00:00
instance: kb-cron
parent: social-heuristics-20260505-0
summary:
Social heuristics are simple decision making strategies that guide people's behavior and decisions in the social environment when time, information, or cognitive resources are scarce. Social environments tend to be characterised by complexity and uncertainty, and in order to simplify the decision-making process, people may use heuristics, which are decision making strategies that involve ignoring some information or relying on simple rules of thumb. The class of phenomena described by social heuristics overlap with those typically investigated by social psychology and game theory. At the intersection of these fields, social heuristics have been applied to explain cooperation in economic games used in experimental research. In the view of the field's academics, cooperation is typically advantageous in daily life, and therefore people develop a cooperation heuristic that gets applied even to one-shot anonymous interactions (the "social heuristics hypothesis" of human cooperation). == Overview == === Bounded rationality === In the decision-making process, optimisation is almost always intractable in any implementation, whether machine or neural. Because of this, defined parameters or boundaries must be implemented in the process in order to achieve an acceptable outcome. This method is known as applying bounded rationality, where an individual makes a collective and rational choice


id: social-heuristics-20260505-1
file: data/en.wikipedia.org/wiki/Social_heuristics-1.md
category: reference
title: Social heuristics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Social_heuristics
date_saved: 2026-05-05T09:58:38.808102+00:00
instance: kb-cron
parent: social-heuristics-20260505-0
summary:
Imitate-the-majority heuristic, also referred to follow-the-majority heuristic. An agent (or decision maker) using the heuristic would imitate the behavior of the majority of others in his reference group. For instance, in deciding which restaurant to choose, people tend to choose the one with the longer waiting queue. Imitate-the-successful heuristic, also referred to follow-the-best heuristic. An agent using the heuristic would imitate the behavior of the most successful person in her reference group. Equity heuristic, also referred to 1/N heuristic. Using the heuristic means equally distributing resources among the available options. The heuristic was found to be successful in the stock market and also been found to describe parental resource allocation decisions: parents typically allocate their time and effort equally amongst their children. Social-circle heuristic. The heuristic is used to infer which of two alternatives has the higher value. An agent using the heuristic would search through her social circles in order of their proximity to the self (self, family, friends, and acquaintances), stopping the search as soon as the number of instances of one alternative within a circle exceeds that of the other, choosing the alternative with the higher tally. For example, a person might decide which of two sports


id: social-heuristics-20260505-2
file: data/en.wikipedia.org/wiki/Social_heuristics-2.md
category: reference
title: Social heuristics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Social_heuristics
date_saved: 2026-05-05T09:58:38.808102+00:00
instance: kb-cron
parent: social-heuristics-20260505-0
summary:
Prisoner's dilemma game: two players each decide whether to cooperate or defect; a player who defects when the other cooperates maximizes his payout, if both cooperate the payout is higher than if both defect. Public goods game : multiple players each choose how much money to put towards a public project; the amount in the public pot is increased by a given factor and distributed equally to the players. Trust game: one player transfers money to another player and the money is increased by a given factor; the other then decides whether and how much to transfer back. Ultimatum game: one player makes an offer for how to split a resource with the other player; the other player can accept the offer (so that both players get the amount proposed by the split) or reject the offer (so that neither player gets anything). These economic games all share the condition that, when played in a single round, an individual's payout is maximized if he acts selfishly and chooses not to cooperate. However, over the course of repeated rounds, cooperation can be payout maximizing and thus be a self-interested strategy. Following a dual-process framework, the social heuristics hypothesis contends that cooperation,


id: sutton-s-law-20260505-0
file: data/en.wikipedia.org/wiki/Sutton's_law-0.md
category: reference
title: Sutton's law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sutton's_law
date_saved: 2026-05-05T09:58:39.965896+00:00
instance: kb-cron
parent: sutton-s-law-20260505-0
summary:
Sutton's law states that when diagnosing, one should first consider the obvious. It suggests that one should first conduct those tests which could confirm (or rule out) the most likely diagnosis. It is taught in medical schools to suggest to medical students that they might best order tests in that sequence which is most likely to result in a quick diagnosis, hence treatment, while minimizing unnecessary costs. It is also applied in pharmacology, when choosing a drug to treat a specific disease you want the drug to reach the disease. It is applicable to any process of diagnosis, e.g., debugging computer programs. Computer-aided diagnosis provides a statistical and quantitative approach. A more thorough analysis will consider the false positive rate of the test and the possibility that a less likely diagnosis might have more serious consequences. A competing principle is the idea of performing simple tests before more complex and expensive tests, moving from bedside tests to blood results and simple imaging such as ultrasound and then more complex such as MRI then specialty imaging. The law can also be applied in prioritizing tests when resources are limited, so a test for a treatable condition should be performed before an


id: symmetry-in-problem-solving-20260505-0
file: data/en.wikipedia.org/wiki/Symmetry_in_problem_solving-0.md
category: reference
title: Symmetry in problem solving
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Symmetry_in_problem_solving
date_saved: 2026-05-05T09:58:41.134584+00:00
instance: kb-cron
parent: symmetry-in-problem-solving-20260505-0
summary:
Symmetry in problem solving is one of the general methods used in mathematics and science to solve problems. Problem solving plays a large part in the teaching of mathematics, science and engineering. The use of symmetry as one of a number of problem solving strategies (heuristics) was first stated in 1945 by George Pólya in his book How to solve it. == Usage == Symmetry can be used in a variety of ways to assist in problem solving. Visualisation: by visualising the problem sometimes symmetry is revealed which simplifies finding a solution. Visualisation can be done by rearranging the problem expression into a more symmetric form, or by drawing a picture of the problem which reveals hidden symmetrical structure. Diagramming can be used to provide insight into the structure of a problem which may be obscured by its written formulation. Arguing "by symmetry": using a symmetry argument often clarifies a problem, leading to a quicker solution. For example, algebraic symmetry allows the permutation of the variables in an equation without changing it. Simplification: algebraic expressions and equations often benefit from simplification using symmetry. An example is the use of substitutions in expressions. Another example is switching from Cartesian coordinates to


id: take-the-best-heuristic-20260505-0
file: data/en.wikipedia.org/wiki/Take-the-best_heuristic-0.md
category: reference
title: Take-the-best heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Take-the-best_heuristic
date_saved: 2026-05-05T09:58:42.306420+00:00
instance: kb-cron
parent: take-the-best-heuristic-20260505-0
summary:
In psychology, the take-the-best heuristic is a heuristic (a simple strategy for decision-making) which decides between two alternatives by choosing based on the first cue that discriminates them, where cues are ordered by cue validity (highest to lowest). In the original formulation, the cues were assumed to have binary values (that is, either yes or no) or have an unknown value. The logic of the heuristic is that it bases its choice on the best cue (reason) only and ignores the rest. Psychologists Gerd Gigerenzer and Daniel Goldstein discovered that the heuristic did surprisingly well at making accurate inferences in real-world environments, such as inferring which of two cities is larger. The heuristic has since been modified and applied to domains from medicine, artificial intelligence, and political forecasting. The heuristic has been used to accurately model how experts, such as airport customs officers and professional burglars, make decisions; the model often makes better predictions of human behavior than more complex models that assume experts integrate all available cues. == One-reason decision-making == Theories of decision making typically assume that all relevant reasons (features or cues) are searched and integrated into a final decision. Yet under uncertainty (as opposed to risk),


id: take-the-best-heuristic-20260505-1
file: data/en.wikipedia.org/wiki/Take-the-best_heuristic-1.md
category: reference
title: Take-the-best heuristic
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Take-the-best_heuristic
date_saved: 2026-05-05T09:58:42.306420+00:00
instance: kb-cron
parent: take-the-best-heuristic-20260505-0
summary:
== Take-the-best for the comparison task == Consider the task to infer which object, A {\textstyle A} or B {\textstyle B} , has a higher value on a numerical criterion. As an example imagine someone having to judge whether the German city of Cologne has a larger population than the other German city of Stuttgart. This judgment or inference has to be based on information provided by binary cues, like "Is the city a state capital?". From a formal point of view, the task is a categorization: A pair ( A , B ) {\textstyle \left(A,B\right)} is to be categorized as X A > X B {\textstyle X_{A}>X_{B}} or X B > X A {\textstyle X_{B}>X_{A}} (where X {\textstyle X} denotes the criterion), based on cue information. Cues are binary; this means they assume two values and can be modeled, for instance, as having the values 0 and 1 (for 'yes' and 'no'). They are ranked according to their cue validity, defined as the proportion of correct comparisons among the pairs A {\textstyle A} and B {\textstyle B} , for which it has different values, i.e., for which it discriminates between A {\textstyle A} and B {\textstyle B} . Take-the-best


id: talking-past-each-other-20260505-0
file: data/en.wikipedia.org/wiki/Talking_past_each_other-0.md
category: reference
title: Talking past each other
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Talking_past_each_other
date_saved: 2026-05-05T09:58:43.488635+00:00
instance: kb-cron
parent: talking-past-each-other-20260505-0
summary:
"Talking past each other" is an English phrase sometimes used to describe the situation where two or more people talk about different subjects, while believing that they are talking about the same thing. David Horton wrote that when characters in fiction 'talk past each other,' the effect is to expose "an unbridgeable gulf between their respective perceptions and intentions. The result is an exchange, but never an interchange, of words in fragmented and cramped utterances whose subtext often reveals more than their surface meaning." His usage of single quotes around the phrase indicates the colloquial nature of it. The phrase might be used in widely varying contexts. For example, a book written in 1973, referred to certain dawn-to-dusk discussions of physics between Albert Einstein and David Hilbert in 1917, which they continued in writing, and Felix Klein notes that they "talked past each other, as happens not infrequently between simultaneously producing mathematicians." == See also == Essentially contested concept – Problem in philosophy Semantic change – Evolution of a word's meaning Contronym – Word that has two opposing meanings Irrelevant conclusion – Type of informal fallacy == Notes == == References == Anderson, Philip Warren. "Twenty years of talking past


id: teachable-moment-20260505-0
file: data/en.wikipedia.org/wiki/Teachable_moment-0.md
category: reference
title: Teachable moment
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Teachable_moment
date_saved: 2026-05-05T09:58:44.652442+00:00
instance: kb-cron
parent: teachable-moment-20260505-0
summary:
A teachable moment, in education, is the time at which learning a particular topic or idea becomes possible or easiest. == In education == The concept was popularized by Robert Havighurst in his 1952 book, Human Development and Education. In the context of education theory, Havighurst explained, "A developmental task is a task which is learned at a specific point and which makes achievement of succeeding tasks possible. When the timing is right, the ability to learn a particular task will be possible. This is referred to as a 'teachable moment.' It is important to keep in mind that unless the time is right, learning will not occur. Hence, it is important to repeat important points whenever possible so that when a student's teachable moment occurs, s/he can benefit from the knowledge." The concept pre-dates Havighurst's book, as does the use of the phrase, but he is credited with popularizing it. The phrase sometimes denotes not a developmental stage, but rather "that moment when a unique, high interest situation arises that lends itself to discussion of a particular topic." It implies "personal engagement" with issues and problems. These moments can (and often do) come when least expected. Teachers and parents


id: thinking-fast-and-slow-20260505-0
file: data/en.wikipedia.org/wiki/Thinking,_Fast_and_Slow-0.md
category: reference
title: Thinking, Fast and Slow
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow
date_saved: 2026-05-05T09:58:45.841527+00:00
instance: kb-cron
parent: thinking-fast-and-slow-20260505-0
summary:
Thinking, Fast and Slow is a 2011 popular science book by the Israeli-American psychologist Daniel Kahneman. Its main thesis is a differentiation between two modes of thought: "System 1" is fast, instinctive and emotional; "System 2" is slower, more deliberative, and more logical. The book delineates rational and non-rational motivations or triggers associated with each type of thinking process, and how they complement each other, starting with Kahneman's own research on loss aversion. From framing choices to people's tendency to replace a difficult question with one that is easy to answer, the book summarizes several decades of research to suggest that people have too much confidence in human judgement. Kahneman performed his own research, often in collaboration with the psychologist Amos Tversky, which enriched his experience to write the book. It covers different phases of his career: his early work concerning cognitive biases, his work on prospect theory and happiness, and with the Israel Defense Forces. Jason Zweig, a columnist at The Wall Street Journal, helped write and research the book over two years. The book was a New York Times bestseller and was the 2012 winner of the American National Academies Communication Award for best creative work that helps


id: thinking-fast-and-slow-20260505-1
file: data/en.wikipedia.org/wiki/Thinking,_Fast_and_Slow-1.md
category: reference
title: Thinking, Fast and Slow
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow
date_saved: 2026-05-05T09:58:45.841527+00:00
instance: kb-cron
parent: thinking-fast-and-slow-20260505-0
summary:
=== Conjunction fallacy === System 1 is prone to substituting a simpler question for a difficult one. In what Kahneman terms their "best-known and most controversial" experiment, "the Linda problem", subjects were told about an imaginary Linda, young, single, outspoken, and intelligent, who, as a student, was very concerned with discrimination and social justice. They asked whether it was more probable that Linda is a bank teller or that she is a bank teller and an active feminist. The overwhelming response was that "feminist bank teller" was more likely than "bank teller", violating the laws of probability. (All feminist bank tellers are bank tellers, so the former can't be more likely). In this case System 1 substituted the easier question, "Is Linda a feminist?", neglecting the occupation qualifier. An alternative interpretation is that the subjects added an unstated cultural implicature to the effect that the other answer implied an exclusive or, that Linda was not a feminist. === Optimism and loss aversion === Kahneman writes of a "pervasive optimistic bias", which "may well be the most significant of the cognitive biases." This bias generates the illusion of control: the illusion that we have substantial control of our lives. A natural


id: thinking-fast-and-slow-20260505-2
file: data/en.wikipedia.org/wiki/Thinking,_Fast_and_Slow-2.md
category: reference
title: Thinking, Fast and Slow
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow
date_saved: 2026-05-05T09:58:45.841527+00:00
instance: kb-cron
parent: thinking-fast-and-slow-20260505-0
summary:
"Odd as it may seem," Kahneman writes, "I am my remembering self, and the experiencing self, who does my living, is like a stranger to me." === Experienced well-being === Kahneman first began the study of well-being in the 1990s. At the time most happiness research relied on polls about life satisfaction. Having previously studied unreliable memories, the author was doubtful that life satisfaction was a good indicator of happiness. He designed a question that emphasized instead the well-being of the experiencing self. The author proposed that "Helen was happy in the month of March" if she spent most of her time engaged in activities that she would rather continue than stop, little time in situations that she wished to escape, and not too much time in a neutral state that wouldn't prefer continuing or stopping the activity either way. === Thinking about life === Kahneman suggests that emphasizing a life event such as a marriage or a new car can provide a distorted illusion of its true value. This "focusing illusion" revisits earlier ideas of substituting difficult questions and WYSIATI. == Awards and honors == 2011 Los Angeles Times Book Prize (Current Interest) National Academy of Sciences Best Book


id: trial-and-error-20260505-0
file: data/en.wikipedia.org/wiki/Trial_and_error-0.md
category: reference
title: Trial and error
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Trial_and_error
date_saved: 2026-05-05T09:58:47.060591+00:00
instance: kb-cron
parent: trial-and-error-20260505-0
summary:
Trial and error is a fundamental method of problem-solving characterized by repeated, varied attempts which are continued until success, or until the practitioner stops trying. According to W.H. Thorpe, the term was devised by C. Lloyd Morgan (1852–1936) after trying out similar phrases "trial and failure" and "trial and practice". However, the phrase 'trial and error' was already in use in 1833, where it can be found in the book title "Practical Methods by Trial and Error for Finding the Latitude and Time at Sea". Under Morgan's Canon, animal behaviour should be explained in the simplest possible way. Where behavior seems to imply higher mental processes, it might be explained by trial-and-error learning. An example is the skillful way in which his terrier Tony opened the garden gate, easily misunderstood as an insightful act by someone seeing the final behavior. Lloyd Morgan, however, had watched and recorded the series of approximations by which the dog had gradually learned the response, and could demonstrate that no insight was required to explain it. Edward Lee Thorndike was the initiator of the theory of trial and error learning based on the findings he showed how to manage a trial-and-error experiment in the laboratory.


id: trial-and-error-20260505-1
file: data/en.wikipedia.org/wiki/Trial_and_error-1.md
category: reference
title: Trial and error
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Trial_and_error
date_saved: 2026-05-05T09:58:47.060591+00:00
instance: kb-cron
parent: trial-and-error-20260505-0
summary:
solution-oriented: trial and error does not attempt to discover why a solution works, merely that it is a solution. problem-specific: trial and error does not attempt to generalize a solution to other problems. non-optimal: trial and error is generally an attempt to find a solution, not all solutions, and not the best solution. needs little knowledge: trial and error can proceed where there is little or no knowledge of the subject. It is possible to use trial and error to find all solutions or the best solution when a testably finite number of possible solutions exists. To find all solutions, one simply makes a note and continues, rather than ending the process when a solution is found, until all solutions have been tried. To find the best solution, one finds all solutions by the method just described and then comparatively evaluates them based upon some predefined set of criteria, the existence of which is a condition for the possibility of finding a best solution. (Also, when only one solution can exist, as in assembling a jigsaw puzzle, then any solution found is the only solution and so is necessarily the best.) == Examples == Trial and error has traditionally been


id: win-stay-lose-switch-20260505-0
file: data/en.wikipedia.org/wiki/Win–stay,_lose–switch-0.md
category: reference
title: Win–stay, lose–switch
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Win–stay,_lose–switch
date_saved: 2026-05-05T09:58:48.259441+00:00
instance: kb-cron
parent: win-stay-lose-switch-20260505-0
summary:
In psychology, game theory, statistics, and machine learning, win–stay, lose–switch (also win–stay, lose–shift), or Pavlov, (named after Ivan Pavlov) is a heuristic learning strategy used to model learning in decision situations. It was first invented as an improvement over randomization in bandit problems. It was later applied to the prisoner's dilemma in order to model the evolution of altruism. In most versions, it starts either with a cooperate, then proceeds as always, or starts with a "probe" of cooperate-defect-cooperate to determine the other player's strategy. A mutual cooperation is regarded as a win. The learning rule bases its decision only on the outcome of the previous play. Outcomes are divided into successes (wins) and failures (losses). If the play on the previous round resulted in a success, then the agent plays the same strategy on the next round. Alternatively, if the play resulted in a failure the agent switches to another action. A large-scale empirical study of players of the game rock, paper, scissors shows that a variation of this strategy is adopted by real-world players of the game, instead of the Nash equilibrium strategy of choosing entirely at random between the three options. == References == == See also


id: zero-sum-thinking-20260505-0
file: data/en.wikipedia.org/wiki/Zero-sum_thinking-0.md
category: reference
title: Zero-sum thinking
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Zero-sum_thinking
date_saved: 2026-05-05T09:58:49.475318+00:00
instance: kb-cron
parent: zero-sum-thinking-20260505-0
summary:
Zero-sum thinking perceives situations as zero-sum games, where one person's gain would be another's loss. The term is derived from game theory. However, unlike the game theory concept, zero-sum thinking refers to a psychological construct—a person's subjective interpretation of a situation. Zero-sum thinking is captured by the saying "your gain is my loss" (or conversely, "your loss is my gain"). Rozycka-Tran et al. (2015) defined zero-sum thinking as: A general belief system about the antagonistic nature of social relations, shared by people in a society or culture and based on the implicit assumption that a finite amount of goods exists in the world, in which one person's winning makes others the losers, and vice versa ... a relatively permanent and general conviction that social relations are like a zero-sum game. People who share this conviction believe that success, especially economic success, is possible only at the expense of other people's failures. Zero-sum bias is a cognitive bias towards zero-sum thinking; it is people's tendency to intuitively judge that a situation is zero-sum, even when this is not the case. This bias promotes zero-sum fallacies — false beliefs that situations are zero-sum. Such fallacies can cause other false judgements and poor


id: zero-sum-thinking-20260505-1
file: data/en.wikipedia.org/wiki/Zero-sum_thinking-1.md
category: reference
title: Zero-sum thinking
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Zero-sum_thinking
date_saved: 2026-05-05T09:58:49.475318+00:00
instance: kb-cron
parent: zero-sum-thinking-20260505-0
summary:
==== Resource-scarce environments ==== One of the proximate causes of zero-sum thinking is the experiences that individuals have with scarce resources or zero-sum interactions in their developmental environment. In 1965, George M. Foster argued that members of "peasant" societies have an "Image of Limited Good," which he argued was learned through by experiences in a society that was essentially zero-sum."The model of cognitive orientation that seems to me best to account for peasant behavior is the "Image of Limited Good." By "Image of Limited Good" I mean that broad areas of peasant behavior are patterned in such fashion as to suggest that peasants view their social, economic, and natural universes—their total environment—as one in which all of the desired things in life such as land, wealth, health, friendship and love, manliness and honor, respect and status, power and influence, security and safety, exist in finite quantity and are always in short supply, as far as the peasant is concerned. Not only do these and all other "good things" exist in finite and limited quantities, but in addition there is no way directly within peasant power to increase the available quantities ... When the peasant views his economic world as one


id: hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Hypothesis-0.md
category: reference
title: Hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hypothesis
date_saved: 2026-05-05T09:58:51.041584+00:00
instance: kb-cron
parent: hypothesis-20260505-0
summary:
A hypothesis (pl.: hypotheses) is a proposed explanation for a phenomenon. A scientific hypothesis must be based on observations and make a testable and reproducible prediction about reality, in a process beginning with an educated guess. If a hypothesis is repeatedly independently demonstrated by experiment to be true, it becomes a scientific theory. In colloquial usage, the words hypothesis and theory are often used interchangeably, but this is incorrect in the context of science. A working hypothesis is a provisionally-accepted hypothesis used for the purpose of pursuing further progress in research. Working hypotheses are frequently discarded, and often proposed with knowledge (and warning) that they are incomplete and thus false, with the intent of moving research in at least somewhat the right direction, especially when scientists are stuck on an issue and brainstorming ideas. In formal logic, a hypothesis is the antecedent in a proposition. For example, in the proposition "If P, then Q", statement P denotes the hypothesis (or antecedent) of the consequent Q. Hypothesis P is the assumption in a (possibly counterfactual) "what if" question. The adjective "hypothetical" (having the nature of a hypothesis or being assumed to exist as an immediate consequence of a hypothesis), can refer


id: hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Hypothesis-1.md
category: reference
title: Hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hypothesis
date_saved: 2026-05-05T09:58:51.041584+00:00
instance: kb-cron
parent: hypothesis-20260505-0
summary:
A working hypothesis is a hypothesis that is provisionally accepted as a basis for further research in the hope that a tenable theory will be produced, even if the hypothesis ultimately fails. Like all hypotheses, a working hypothesis is constructed as a statement of expectations, which can be linked to the exploratory research purpose in empirical investigation. Working hypotheses are often used as a conceptual framework in qualitative research. The provisional nature of working hypotheses makes them useful as an organizing device in applied research. Here they act like a useful guide to address problems that are still in a formative phase. In recent years, philosophers of science have tried to integrate the various approaches to evaluating hypotheses, and the scientific method in general, to form a more complete system that integrates the individual concerns of each approach. Notably, Imre Lakatos and Paul Feyerabend, Karl Popper's colleague and student, respectively, have produced novel attempts at such a synthesis. == Hypotheses, concepts and measurement == Concepts in Hempel's deductive-nomological model play a key role in the development and testing of hypotheses. Most formal hypotheses connect concepts by specifying the expected relationships between propositions. When a set of hypotheses are grouped together,


id: absolute-income-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Absolute_income_hypothesis-0.md
category: reference
title: Absolute income hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Absolute_income_hypothesis
date_saved: 2026-05-05T09:58:52.235761+00:00
instance: kb-cron
parent: absolute-income-hypothesis-20260505-0
summary:
In economics, the absolute income hypothesis concerns how a consumer divides their disposable income between consumption and saving. It is part of the theory of consumption attributed to John Maynard Keynes. The American economist James Tobin (1918–2002) researched and developed this idea more extensively in the 1960s and 70s. == Background == Keynes' General Theory in 1936 identified the relationship between income and consumption as a key macroeconomic relationship. Keynes asserted that real consumption (i.e. adjusted for inflation) is a function of real disposable income, which is total income net of taxes. As income rises, the theory asserts that consumption will also rise, but not necessarily at the same rate. When applied to a cross section of a population, rich people are expected to consume a lower proportion of their income than poor people. The marginal propensity to consume is present in Keynes' consumption theory and determines by what amount consumption will change in response to a change in income. While this theory has success modeling consumption in the short term, attempts to apply this model over a longer time frame have proven less successful. This has led to the absolute income hypothesis falling out of favor as the consumption


id: ad-hoc-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Ad_hoc_hypothesis-0.md
category: reference
title: Ad hoc hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Ad_hoc_hypothesis
date_saved: 2026-05-05T09:58:53.374609+00:00
instance: kb-cron
parent: ad-hoc-hypothesis-20260505-0
summary:
In science and philosophy, an ad hoc hypothesis is a hypothesis added to a theory in order to save it from being falsified. For example, a person that wants to believe in leprechauns can avoid ever being proven wrong by using ad hoc hypotheses (e.g., by adding "they are invisible", then "their motives are complex", and so on). Often, ad hoc hypothesizing is employed to compensate for anomalies not anticipated by the theory in its unmodified form. == In the scientific community == Scientists are often skeptical of theories that rely on frequent, unsupported adjustments to sustain them. This is because, if a theorist so chooses, there is no limit to the number of ad hoc hypotheses that they could add. Thus the theory becomes more and more complex, but is never falsified. This is often at a cost to the theory's predictive power, however. Ad hoc hypotheses are often characteristic of pseudoscientific subjects. Albert Einstein's addition of the cosmological constant to general relativity in order to allow a static universe was ad hoc. Although he later referred to it as his "greatest blunder", it may correspond to theories of dark energy. == See also == Ad hoc Fringe science


id: adipose-tissue-expandability-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Adipose_tissue_expandability_hypothesis-0.md
category: reference
title: Adipose tissue expandability hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Adipose_tissue_expandability_hypothesis
date_saved: 2026-05-05T09:58:55.612615+00:00
instance: kb-cron
parent: adipose-tissue-expandability-hypothesis-20260505-0
summary:
The adipose tissue expandability hypothesis posits that metabolic dysregulation that appears to be caused by excess weight, such as type 2 diabetes and non-alcoholic fatty liver disease, are triggered when an individual's capacity for storing excess calories in the subcutaneous adipose tissue is exceeded. Each individual's capacity to store excess energy varies, so the threshold at which an individual begins to experience metabolic disease is not well captured by methods such as body mass index or body fat percentage. If a person has the ability to store a large amount of body fat without experiencing metabolic disturbance, this is known as metabolically healthy obesity. Although it was hypothesized that having a larger number of smaller adipocytes was correlated with the ability to store more fat, some evidence suggests the opposite—those with smaller adipocytes having a worse metabolic profile. The core factor, the inability to store excess fat in these cells, remains. == References ==


id: aestivation-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Aestivation_hypothesis-0.md
category: reference
title: Aestivation hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Aestivation_hypothesis
date_saved: 2026-05-05T09:58:56.818197+00:00
instance: kb-cron
parent: aestivation-hypothesis-20260505-0
summary:
The aestivation hypothesis is a hypothesized solution to the Fermi paradox conceived in 2017 by Anders Sandberg, Stuart Armstrong and Milan M. Ćirković. The hypothesis, published on 27 April 2017, suggests advanced alien civilizations may be storing energy and aestivating (hibernating in times of heat instead of cold), until the universe cools to better make use of the stored energy to perform tasks. As the universe cools, the potential work producible by stored energy can increase by a multiplier of 1030 per Landauer's principle. If the goal of an advanced civilization is to maximize the number of calculations done, to generate information processing for tasks like mass-producing simulations, then aestivation would be purposeful to achieve this end. == Fermi paradox == There is no reliable or reproducible evidence that aliens have visited Earth. No transmissions or evidence of intelligent extraterrestrial life have been detected or observed anywhere other than Earth in the Universe. This runs counter to the knowledge that the Universe is filled with a very large number of planets, some of which likely hold the conditions hospitable for life. Life typically expands until it fills all available niches. These contradictory facts form the basis for the Fermi paradox,


id: alvarez-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Alvarez_hypothesis-0.md
category: reference
title: Alvarez hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Alvarez_hypothesis
date_saved: 2026-05-05T09:58:58.010084+00:00
instance: kb-cron
parent: alvarez-hypothesis-20260505-0
summary:
The Alvarez hypothesis posits that the mass extinction of the non-avian dinosaurs and many other living things during the Cretaceous–Paleogene extinction event was caused by the impact of a large asteroid on the Earth. Prior to 2013, it was commonly cited as having happened about 65 million years ago, but Renne and colleagues (2013) gave an updated value of 66 million years. Evidence indicates that the asteroid fell in the Yucatán Peninsula, at Chicxulub, Mexico. The hypothesis is named after the father-and-son team of scientists Luis and Walter Alvarez, who first suggested it in 1980. Shortly afterwards, and independently, the same was suggested by Dutch paleontologist Jan Smit. In March 2010, an international panel of scientists endorsed the asteroid hypothesis, specifically the Chicxulub impact, as being the cause of the extinction. A team of 41 scientists reviewed 20 years of scientific literature and in so doing also ruled out other theories such as massive volcanism. They had determined that a space rock 10–15 km (6–9 mi) in diameter hurtled into earth at Chicxulub. For comparison, the Martian moon Phobos has a diameter of 22 km (14 mi), and Mount Everest is just under 9 km (5.6 mi). The collision would


id: alvarez-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Alvarez_hypothesis-1.md
category: reference
title: Alvarez hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Alvarez_hypothesis
date_saved: 2026-05-05T09:58:58.010084+00:00
instance: kb-cron
parent: alvarez-hypothesis-20260505-0
summary:
The location of the impact was unknown when the Alvarez team developed their hypothesis, but later scientists discovered the Chicxulub Crater in the Yucatán Peninsula, now considered the likely impact site. Paul Renne of the Berkeley Geochronology Center has reported that the date of the asteroid event is 66,038,000 years ago, plus or minus 11,000 years, based on Ar-Ar dating. He further posits that the mass extinction of dinosaurs occurred within 33,000 years of this date. In April 2019, a paper was published in PNAS which describes evidence from a fossil site in North Dakota that the authors say provides a "postimpact snapshot" of events after the asteroid collision "including ejecta accretion and faunal mass death". The team found that the tektites that had peppered the area were present in amber found on the site and were also embedded in the gills of about 50 percent of the fossil fish. They were also able to find traces of iridium. The authors – who include Walter Alvarez – postulate that shock of the impact, equivalent to an earthquake of magnitude 10 or 11, may have led to seiches, oscillating movements of water in lakes, bays, or gulfs, that would have reached


id: alvarez-hypothesis-20260505-2
file: data/en.wikipedia.org/wiki/Alvarez_hypothesis-2.md
category: reference
title: Alvarez hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Alvarez_hypothesis
date_saved: 2026-05-05T09:58:58.010084+00:00
instance: kb-cron
parent: alvarez-hypothesis-20260505-0
summary:
Although a 2010 paper published in Science that declared that the extinction of the dinosaurs was caused by Chicxulub was co-authored by 41 scientists, dozens of other scientists challenged both the paper's methods and its conclusions. A leading critic of the Alvarez hypothesis is Gerta Keller, who has focused on Deccan Traps volcanism as a likely cause of a more gradual extinction. Despite the fact that the Alvarez hypothesis has overwhelming support from the scientific community, Keller has continued to advocate for research into alternate theories. The Deccan Traps theory was first proposed in 1978 by geologist Dewey McLean but quickly lost traction. The Deccan Traps are an area of volcanic flood basalts in Western India spanning ~1.3 million square kilometers that were created by massive volcanic activity during the same time period in which the Chicxulub impact occurred. Prior to Keller's research, the timeframe of the Deccan Traps' eruptions had a significantly large range of error, making it difficult to draw strong conclusions regarding their connection to the K-Pg extinction. In a 2014 report, Keller and her colleagues used uranium-lead zircon geochronology to more accurately identify the eruptions as occurring both within a span of one million years and


id: analysis-of-competing-hypotheses-20260505-0
file: data/en.wikipedia.org/wiki/Analysis_of_competing_hypotheses-0.md
category: reference
title: Analysis of competing hypotheses
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Analysis_of_competing_hypotheses
date_saved: 2026-05-05T09:58:59.135316+00:00
instance: kb-cron
parent: analysis-of-competing-hypotheses-20260505-0
summary:
The analysis of competing hypotheses (ACH) is a methodology for evaluating multiple competing hypotheses for observed data. It was developed by Richards (Dick) J. Heuer, Jr., a 45-year veteran of the Central Intelligence Agency, in the 1970s for use by the Agency. ACH is used by analysts in various fields who make judgments that entail a high risk of error in reasoning. ACH aims to help an analyst overcome, or at least minimize, some of the cognitive limitations that make prescient intelligence analysis so difficult to achieve. ACH was a step forward in intelligence analysis methodology, but it was first described in relatively informal terms. Producing the best available information from uncertain data remains the goal of researchers, tool-builders, and analysts in industry, academia and government. Their domains include data mining, cognitive psychology and visualization, probability and statistics, etc. Abductive reasoning is an earlier concept with similarities to ACH. == Process == Heuer outlines the ACH process in considerable depth in his book, Psychology of Intelligence Analysis. It consists of the following steps: Hypothesis – The first step of the process is to identify all potential hypotheses, preferably using a group of analysts with different perspectives to brainstorm the possibilities.


id: analysis-of-competing-hypotheses-20260505-1
file: data/en.wikipedia.org/wiki/Analysis_of_competing_hypotheses-1.md
category: reference
title: Analysis of competing hypotheses
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Analysis_of_competing_hypotheses
date_saved: 2026-05-05T09:58:59.135316+00:00
instance: kb-cron
parent: analysis-of-competing-hypotheses-20260505-0
summary:
ACH demands that the analyst makes too many discrete judgments, a great many of which contribute little if anything to discerning the best hypothesis ACH misconceives the nature of the relationship between items of evidence and hypotheses by supposing that items of evidence are, on their own, consistent or inconsistent with hypotheses. ACH treats the hypothesis set as "flat", i.e. a mere list, and so is unable to relate evidence to hypotheses at the appropriate levels of abstraction ACH cannot represent subordinate argumentation, i.e. the argumentation bearing up on a piece of evidence. ACH activities at realistic scales leave analysts disoriented or confused. Van Gelder proposed hypothesis mapping (similar to argument mapping) as an alternative to ACH. === Structured analysis of competing hypotheses === The structured analysis of competing hypotheses offers analysts an improvement over the limitations of the original ACH. The SACH maximizes the possible hypotheses by allowing the analyst to split one hypothesis into two complex ones. For example, two tested hypotheses could be that Iraq has WMD or Iraq does not have WMD. If the evidence showed that it is more likely there are WMDs in Iraq then two new hypotheses could be formulated: WMD are in


id: anfinsen-s-dogma-20260505-0
file: data/en.wikipedia.org/wiki/Anfinsen's_dogma-0.md
category: reference
title: Anfinsen's dogma
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Anfinsen's_dogma
date_saved: 2026-05-05T09:59:00.330938+00:00
instance: kb-cron
parent: anfinsen-s-dogma-20260505-0
summary:
Anfinsen's dogma, also known as the thermodynamic hypothesis, is a postulate in molecular biology. It states that, at least for a small globular protein in its standard physiological environment, the native structure is determined only by the protein's amino acid sequence. The dogma was championed by the Nobel Prize Laureate Christian B. Anfinsen from his research on the folding of ribonuclease A. His research was based on previous studies by biochemist Lisa Steiner, whose superiors at the time did not recognize the significance. The postulate amounts to saying that, at the environmental conditions (temperature, solvent concentration and composition, etc.) at which folding occurs, the native structure is a unique, stable and kinetically accessible minimum of the free energy. In other words, there are three conditions for formation of a unique protein structure: Uniqueness – Requires that the sequence does not have any other configuration with a comparable free energy. Hence the free energy minimum must be unchallenged. Stability – Small changes in the surrounding environment cannot give rise to changes in the minimum configuration. This can be pictured as a free energy surface that looks more like a funnel (with the native state in the bottom of it) rather than


id: aramaic-new-testament-hypotheses-20260505-0
file: data/en.wikipedia.org/wiki/Aramaic_New_Testament_hypotheses-0.md
category: reference
title: Aramaic New Testament hypotheses
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Aramaic_New_Testament_hypotheses
date_saved: 2026-05-05T09:59:01.547733+00:00
instance: kb-cron
parent: aramaic-new-testament-hypotheses-20260505-0
summary:
Aramaic New Testament hypotheses are a number of hypotheses within Biblical scholarship which argue that the Christian New Testament derives in some form from an Aramaic original. A first version was initially advanced in the 17th and 18th centuries, arguing that all Gospels and Acts could derive from one Aramaic proto-Gospel. Subsequent current-day hypotheses trying to better establish this earlier hypothesis, usually argue some parts of the Gospels could derive from an Aramaic sayings-source. In current scholarship they enjoy no notable support compared to the consensus hypothesis that the New Testament was written in Koine Greek. They are related to and often overlap with the Hebrew Gospel hypothesis, which posits a similar idea but with Hebrew instead of Aramaic. == Greek original New Testament hypothesis == The current consensus view held by almost all scholars of the New Testament is that all of its contents were originally written in Koine Greek. An example of how mainstream scholars have dealt with Aramaic influences within an overall view of the Gospels' original Greek-language development may be found in Martin Hengel's synthesis of studies of the linguistic situation in Palestine during the time of Jesus and the Gospels:Since non-literary, simple Greek knowledge or


id: augustinian-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Augustinian_hypothesis-0.md
category: reference
title: Augustinian hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Augustinian_hypothesis
date_saved: 2026-05-05T09:59:02.720328+00:00
instance: kb-cron
parent: augustinian-hypothesis-20260505-0
summary:
The Augustinian hypothesis (sometimes referred to as the Augustinian Proposal) is a solution to the synoptic problem, which concerns the origin of the Gospels of the New Testament. The hypothesis holds that Matthew was written first, by Matthew the Evangelist (see the Gospel According to the Hebrews and the Jewish-Christian Gospels). Mark the Evangelist wrote the Gospel of Mark second and used Matthew and the preaching of Peter as sources. Luke the Evangelist wrote the Gospel of Luke and was aware of the two Gospels that preceded him. Unlike some competing hypotheses, this hypothesis does not rely on, nor does it argue for, the existence of any document that is not explicitly mentioned in historical testimony. Instead, the hypothesis draws primarily upon historical testimony, rather than textual criticism, as the central line of evidence. The foundation of evidence for the hypothesis is the writings of the Church Fathers: historical sources dating back to as early as the first half of the 2nd century, which have been held as authoritative by most Christians for nearly two millennia. Adherents to the Augustinian hypothesis view it as a simple, coherent solution to the synoptic problem. The Augustinian hypothesis addresses certain fundamental points of


id: augustinian-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Augustinian_hypothesis-1.md
category: reference
title: Augustinian hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Augustinian_hypothesis
date_saved: 2026-05-05T09:59:02.720328+00:00
instance: kb-cron
parent: augustinian-hypothesis-20260505-0
summary:
=== Papias === According to Irenaeus, Papias was "a hearer of John and a companion of Polycarp, a man of primitive times," who wrote a volume in "five books." The benefit of historical immediacy, as argued by D. H. Fischer is one of the key determinants of historicity, and the church father Papias is a very early source in regard to testimony that the Matthew wrote his gospel first. Papias wrote that: "Matthew compiled the sayings in the Hebrew language, and everyone translated them as well he could." (The 'Hebrew language' referred to by Papias has often been interpreted as Aramaic.) It has been argued, because Papias does not cite an authority for his assertions concerning Matthew but does concerning Mark, that Matthew was already fully accepted at the time of his writings. === Clement === Eusebius also recorded an important tradition from Clement of Alexandria (died c. 213): In the same volumes Clement has found room for a tradition of the primitive authorities of the Church regarding the order of the gospels. It is this. He used to say that the earliest gospels were those containing the genealogies [Matthew, Luke], while Mark's originated as follows: When, at Rome, Peter


id: augustinian-hypothesis-20260505-2
file: data/en.wikipedia.org/wiki/Augustinian_hypothesis-2.md
category: reference
title: Augustinian hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Augustinian_hypothesis
date_saved: 2026-05-05T09:59:02.720328+00:00
instance: kb-cron
parent: augustinian-hypothesis-20260505-0
summary:
The Augustinian position, and the similar Griesbach hypothesis, has drawn recent interest, especially from B. C. Butler, John Wenham, W.R. Farmer, and others as an alternative solution to the synoptic problem, and has been employed as a scholarly refutation of Marcan priority, the Q hypothesis, and the two-source hypothesis. Butler argued that accepting the priority of Matthew rendered it possible to dispense with the hypothetical Q document altogether, a position he supported by arguments concerning the inadmissibility of appealing to Q as a sound explanation of the cases where Matthew appears to be more original than Mark. Likewise it has been pointed out that differences between the Synoptic Gospels are as easily explained by differing purposes of the authors than by forced redactions or omissions due to ignorance. Furthermore, against certain arguments that the “primitiveness” of the ideas within the Gospels is the determining factor in their literary interdependence, it is observed that defining "primitiveness" carries obvious difficulties. Farmer argued that a modification of the Augustinian hypothesis, the so-called Two-gospel hypothesis, ordering Matthew-Luke-Mark, eliminated all reasons for the existence of Q, a position whose credibility was conceded by W.C. Allen and others. Bernard Orchard also developed the Two-gospel hypothesis and


id: augustinian-hypothesis-20260505-3
file: data/en.wikipedia.org/wiki/Augustinian_hypothesis-3.md
category: reference
title: Augustinian hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Augustinian_hypothesis
date_saved: 2026-05-05T09:59:02.720328+00:00
instance: kb-cron
parent: augustinian-hypothesis-20260505-0
summary:
A savage persecution of the Church, begun by Herod Agrippa I in AD 42, was the signal for the dispersion of the apostles now possessing in the Gospel of Matthew the necessary tool to support and confirm their preaching, while at the same time preserving their theological unity. The first phase was completed, and the second phase of the Church's expansion was about to begin with the mission of Paul. Central to Orchard's characterization of this new second phase is the distinction between a primarily Hebrew orientation and a primarily Greek orientation, focusing not only on the Jewish converts to Christianity, but to the gentile converts as well. This, he argues, resulted in three key events: the translation of the original Matthew into Greek, the production of the Gospel of Mark within the context of Peter's preaching to Greek speaking converts in Rome, and Luke's authorship of his Gospel under the instruction of Paul. Cited in support of this are the comments of Clement, Irenaeus, and others who state that the Gospel of Mark was written by Mark, a follower of the apostle Peter, based on his speeches. Orchard countered the claim that the Gospel of Mark must have been


id: babble-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Babble_hypothesis-0.md
category: reference
title: Babble hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Babble_hypothesis
date_saved: 2026-05-05T09:59:03.879807+00:00
instance: kb-cron
parent: babble-hypothesis-20260505-0
summary:
In psycholinguistics and leadership studies, the babble hypothesis (demonstratively labelled the babble effect) is a conjecture that posits a strong correlation between the amount or quantity of speaking time an individual has in group settings and their likelihood of emerging as a leader, as commonly opposed to quality of speech. According to the hypothesis, individuals who contribute more verbal input during group interactions are perceived to have increased speaking time which in turn increases likelihood of them being perceived and recognized as leaders. Those individuals who speak more also receive higher ratings on leader, communication and contribution-related measures. == Past research == Research into the idea that emerging leaders talk a lot has been around for a long time, with Bales making this claim in 1950. One of the earliest studies that directly varied the quality and quantity of verbal interaction was by Regula and Julian (1973). They found that variations in the quantity but not in the quality of task contributions affected whether the power to influence others was attributed to an individual. There have since been many studies investigating the extent to which speaking time can predict the emergence of leaders in previously leaderless groups. However, many have


id: berserker-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Berserker_hypothesis-0.md
category: reference
title: Berserker hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Berserker_hypothesis
date_saved: 2026-05-05T09:59:05.161026+00:00
instance: kb-cron
parent: berserker-hypothesis-20260505-0
summary:
The Berserker hypothesis, also known as the deadly probes scenario, is the idea that humans have not yet detected intelligent alien life in the universe because it has been systematically destroyed by a series of lethal Von Neumann probes. The hypothesis is named after the Berserker series of novels (1963–2005) written by Fred Saberhagen. The hypothesis has no single known proposer, and instead is thought to have emerged over time in response to the Hart–Tipler conjecture, the idea that an absence of detectable Von Neumann probes is contrapositive evidence that no intelligent life exists outside of the Solar System. According to the Berserker hypothesis, an absence of such probes is not evidence of life's absence, since interstellar probes could "go berserk" and destroy other civilizations, before self-destructing. In his 1983 paper "The Great Silence", astronomer David Brin summarized the implications of the Berserker hypothesis: it is entirely compatible with all the facts and logic of the Fermi paradox, but would mean that there exists no intelligent life left to be discovered. In the worst case, humanity has already alerted others to its existence, and is next in line to be destroyed. There is no need to struggle to suppress the


id: biophilia-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Biophilia_hypothesis-0.md
category: reference
title: Biophilia hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Biophilia_hypothesis
date_saved: 2026-05-05T09:59:06.376743+00:00
instance: kb-cron
parent: biophilia-hypothesis-20260505-0
summary:
The biophilia hypothesis (also called BET) suggests that humans possess an innate tendency to seek connections with nature and other forms of life. Edward O. Wilson introduced and popularized the hypothesis in his book, Biophilia (1984). He defines biophilia as the "innate tendency to focus on life and lifelike processes". He argued that "to explore and affiliate with life is a deep and complicated process in mental development. To an extent still undervalued in philosophy and religion, our existence depends on this propensity, our spirit is woven from it, hope rises on its currents". Wilson saw modern biology as converging with biophilia: "Modern biology has produced a genuinely new way of looking at the world that is incidentally congenial to the inner direction of biophilia. In other words, instinct is in this rare instance aligned with reason.... to the degree that we come to understand other organisms, we will place a greater value on them, and on ourselves". == Natural affinity for living systems == "Biophilia" is an innate affinity of life or living systems. The term was first used by Erich Fromm to describe a psychological orientation of being attracted to all that is alive and vital. Wilson uses


id: biophilia-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Biophilia_hypothesis-1.md
category: reference
title: Biophilia hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Biophilia_hypothesis
date_saved: 2026-05-05T09:59:06.376743+00:00
instance: kb-cron
parent: biophilia-hypothesis-20260505-0
summary:
Many Indigenous cultures do not draw a sharp distinction between humans and nature. In these traditions, humans may be understood as an integral part of the natural world rather than as separate from it. Human practices and ways of life may be seen to be based in relationships of reciprocity involving all living beings and the environment. At the heart of such belief systems is the concept of kinship, which extends beyond human relationships and includes elements of the natural world. Humans, other animals, plants and soil are seen as dependent on each other for survival and health. For example, the Haudenosaunee people express this idea through a "Thanksgiving Address", a ceremony intended to honor all aspects of nature. Some Indigenous cultures have developed what has been referred to as "traditional ecological knowledge". This may include ostensibly sustainable stewardship practices such as controlled burns of vegetation, as employed in some traditional Native American and Aboriginal Australian societies. In Hawaii, the idea of Aloha_ʻĀina aloha has served as a guide for responsible resource use. Indigenous and animist beliefs typically view nature as sacred. Specific sites, species, or phenomena holding deep significance. Emphasis is put on objectives such as reciprocity and balance.


id: black-sea-deluge-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Black_Sea_deluge_hypothesis-0.md
category: reference
title: Black Sea deluge hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Black_Sea_deluge_hypothesis
date_saved: 2026-05-05T09:59:07.496507+00:00
instance: kb-cron
parent: black-sea-deluge-hypothesis-20260505-0
summary:
The Black Sea deluge is the best known of three hypothetical flood scenarios for the Late Quaternary history of the Black Sea that have been proposed since 1997. One other flood scenario proposes a rapid, even catastrophic, rise in sea level of the Black Sea. The maximum depth of the Bosporus and Dardanelles straits is 110 meters (360 ft) and 103 meters (338 ft), respectively, which would put them above the ocean levels in the Last Glacial Maximum, some 125 meters (410 ft) lower than in present times. The hypothesis is controversial, with other authors arguing for a more gradual inundation of the Black Sea. == History == In 1997, William Ryan, Walter Pitman, Petko Dimitrov, and their colleagues first published the Black Sea deluge hypothesis. They proposed that a catastrophic inflow of Mediterranean seawater into the Black Sea freshwater lake occurred around 7,600 years ago, c. 5600 BCE. As proposed, the Early Holocene Black Sea flood scenario describes events that would have profoundly affected prehistoric settlement in Eastern Europe and adjacent parts of Asia and possibly was the basis of oral history concerning the myth of Noah's flood. Some archaeologists support this theory as an explanation for the lack


id: black-sea-deluge-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Black_Sea_deluge_hypothesis-1.md
category: reference
title: Black Sea deluge hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Black_Sea_deluge_hypothesis
date_saved: 2026-05-05T09:59:07.496507+00:00
instance: kb-cron
parent: black-sea-deluge-hypothesis-20260505-0
summary:
== Counter-arguments == Criticisms of the deluge hypothesis hinge on two main lines of arguments. The first mainly focuses on the water level of the Black Sea: if the magnitude and pace of the rise of the Black Sea level was moderate enough, or if it even outpaced the rise in the Aegean basin (with water flowing, when they reconnected, from the former to the latter as it does now), or if the straits were already opened (at a lower level than now) and the two basins already connected at the time of the hypothesised flood, the catastrophe hypothesis is voided. The second is the lack of archaeological evidence one would expect of a flood, such as impact on geology, wildlife or humans. Since the end of the last glacial period, the global sea level has risen 120 m (390 ft). The flood hypothesis hinges on the geomorphology of the Bosporus since the end of the glacial age. The Black Sea area has been isolated and reconnected many times during the last 500,000 years. Opponents of the deluge hypothesis point to clues that water was flowing out of the Black Sea basin as late as 15,000 years ago. In this


id: black-sea-deluge-hypothesis-20260505-2
file: data/en.wikipedia.org/wiki/Black_Sea_deluge_hypothesis-2.md
category: reference
title: Black Sea deluge hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Black_Sea_deluge_hypothesis
date_saved: 2026-05-05T09:59:07.496507+00:00
instance: kb-cron
parent: black-sea-deluge-hypothesis-20260505-0
summary:
== Further reading == Aksu, Ali E.; Hiscott, Richard N.; Mudie, Peta J.; Rochon, André; Kaminski, Michael A.; Abrajano, Teofilo; Yaşar, Doğan (2002). "Persistent Holocene Outflow from the Black Sea to the Eastern Mediterranean Contradicts Noah's Flood Hypothesis". GSA Today. 12 (5): 4. Bibcode:2002GSAT...12e...4A. doi:10.1130/1052-5173(2002)012<0004:PHOFTB>2.0.CO;2. Yanko-Hombach, Valentina; Gilbert, Allan S.; Panin, Nicolae; Dolukhanov, Pavel M., eds. (2007). The Black Sea Flood Question: Changes in Coastline, Climate, and Human Settlement. doi:10.1007/978-1-4020-5302-3. ISBN 978-1-4020-4774-9. Dimitrov, Petko; Dimitrov, Dimitar (2004). The Black Sea, the Flood and the ancient myths. "Slavena", Varna. doi:10.13140/RG.2.2.18954.16327. Dimitrov, Dimitar Petkov (2010). Geology and Non-traditional resources of the Black Sea. LAP (Lambert Academic Publishing AG), Saarbrucken, Germany. doi:10.13140/RG.2.2.20631.88486. Eris, K.; Ryan, W. B. F.; Cagatay, N.; Sancar, Ü.; Lericolais, G.; Menot, G.; Bard, E. (2008). "The timing and evolution of the post-glacial transgression across the Sea of Marmara shelf south of İstanbul" (PDF). Marine Geology. 243 (1–4): 57–76. doi:10.1016/j.margeo.2007.04.010. Gökaşan, E.; Algan, O.; Tur, H.; Meriç, E.; Türker, A.; Şimşek, M. (2005). "Delta formation at the southern entrance of Istanbul Strait (Marmara sea, Turkey): a new interpretation based on high-resolution seismic stratigraphy". Geo-Marine Letters. 25 (6): 370–377. Bibcode:2005GML....25..370G. doi:10.1007/s00367-005-0215-4. S2CID 130792746. Keith, M.L.; Anderson, G.M. (1963). "Radiocarbon Dating: Fictitious


id: bold-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Bold_hypothesis-0.md
category: reference
title: Bold hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bold_hypothesis
date_saved: 2026-05-05T09:59:08.744356+00:00
instance: kb-cron
parent: bold-hypothesis-20260505-0
summary:
Bold hypothesis (or bold conjecture, the terms are used interchangeably) is a concept originally created by the liberal philosopher Karl Popper when he tried to define the meaning of scientific thinking and scientific progress. It was first explained in his debut The Logic of Scientific Discovery (1935) and subsequently elaborated in writings such as Conjectures and Refutations: The Growth of Scientific Knowledge (1963), Objective knowledge: an evolutionary approach (1972), and Replies to my critics (1974). In successive texts written in the course of four decades, Popper added some nuances to the definition of the concept. Broadly speaking, the idea of a bold hypothesis refers to a new, testable theoretical proposition (or theoretical claim) made within a subject area which, if it is true, would be able to explain and predict much more about the subject than was previously possible. It would significantly alter existing scientific understandings about the subject, in a positive way. The new idea would be very useful for scientific research about the subject. This contrasts with other types of scientific claims which, if they turn out to be true, make little difference to what scientists already know about the subject. The contrary of a bold hypothesis is


id: bold-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Bold_hypothesis-1.md
category: reference
title: Bold hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bold_hypothesis
date_saved: 2026-05-05T09:59:08.744356+00:00
instance: kb-cron
parent: bold-hypothesis-20260505-0
summary:
”There is a reality behind the world as it appears to us, possibly a many-layered reality, of which the appearances are the outermost layers. What the great scientist does is boldly to guess, daringly to conjecture, what these inner realities are like. (…) The boldness can be gauged by the distance between the world of appearance and the conjectured reality, the explanatory hypotheses. But there is another, a special kind of boldness – the boldness of predicting aspects of the world of appearance which so far have been overlooked but which it must possess if the conjectured reality is (more or less) right, if the explanatory hypotheses are (approximately) true. It is this more special kind of boldness which I have usually in mind when I speak of bold scientific conjectures. It is the boldness of a conjecture which takes a real risk – the risk of being tested and refuted; the risk of clashing with reality. Thus my proposal was, and is, that it is this second boldness, together with the readiness to look out for tests and refutations, which distinguishes “empirical” science from nonscience, and especially from prescientific myths and metaphysics.” This passage makes it very clear, that


id: bold-hypothesis-20260505-2
file: data/en.wikipedia.org/wiki/Bold_hypothesis-2.md
category: reference
title: Bold hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bold_hypothesis
date_saved: 2026-05-05T09:59:08.744356+00:00
instance: kb-cron
parent: bold-hypothesis-20260505-0
summary:
Is boldness always a good thing in scientific hypothesizing? How we assess the degree of boldness may just be a subjective matter (it may depends on how you care to look at it). Some new ideas, although they are rather modest in themselves, can make a very large difference to the advancement of scientific research. At a more concrete level, the degree of "boldness" could refer (i) to the content of the hypothesis (considered relative to other possible hypotheses), or (ii) to the manner or context in which the hypothesis is presented, (iii) to its expected importance for research, or (iv) to the attitude involved. The degree of boldness could be downplayed for the sake of credibility or compatibility with established ideas, or it could be exaggerated to create the image of a "big scientific breakthrough" (to obtain research funding). The timing of the evaluation of a hypothesis is also important: a hypothesis which does not seem "bold" right now, could be judged "very bold" later, when historians know much more about the full impact it turned out to have (and vice versa). Alan F. Chalmers comments that “What rates as a bold conjecture at one stage in the history


id: bold-hypothesis-20260505-3
file: data/en.wikipedia.org/wiki/Bold_hypothesis-3.md
category: reference
title: Bold hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bold_hypothesis
date_saved: 2026-05-05T09:59:08.744356+00:00
instance: kb-cron
parent: bold-hypothesis-20260505-0
summary:
A falsified conjecture shows the scientist only "what he does not know" or what cannot be the case. However, in reality scientists are more interested in knowing what is the case, and what they can know. That is, scientists are interested mainly in gaining positive new knowledge, which can be used for practical purposes. Scientists are not primarily interested in “knowing that they don't know things”, or in "knowing what is not the case" (other than to rule out possibilities). Scientists want to know what really is the case. Scientific statements according to this Lakatosian perspective are not falsifiable statements, as Karl Popper claimed, but fallible statements. There is an important difference. Falsifiable ideas are testable ideas which can be definitely proved to be false. Fallible statements are testable statements that could be wrong. Fallible statements include both testable propositions and statements of which it is known that they could be wrong, although currently we do not know how to test them yet for their truth or falsity (or, the possible tests are technically not yet feasible). According to Lakatos, all scientific statements are in reality fallible hypotheses, which scientists at the very least intend or aim to test for


id: broad-spectrum-revolution-20260505-0
file: data/en.wikipedia.org/wiki/Broad_spectrum_revolution-0.md
category: reference
title: Broad spectrum revolution
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Broad_spectrum_revolution
date_saved: 2026-05-05T09:59:09.941400+00:00
instance: kb-cron
parent: broad-spectrum-revolution-20260505-0
summary:
The broad spectrum revolution (BSR) hypothesis, proposed by Kent Flannery in a 1968 paper presented to a London University symposium, suggested that the emergence of the Neolithic in southwest Asia was prefaced by increases in dietary breadth among foraging societies. The broad spectrum revolution followed the last glacial period around 15,000 BP in the Middle East and 12,000 BP in Europe. During this time, there was a transition from focusing on a few main food sources to gathering/hunting a "broad spectrum" of plants and animals. == Hypothesis details == Flannery's hypothesis was meant to help explain the adoption of agriculture in the Neolithic Revolution. Unpersuaded by "the facile explanation of prehistoric environmental change" Flannery suggested (following Lewis Binford's equilibrium model) that population growth in optimal habitats led to demographic pressure within nearby marginal habitats as daughter groups migrated. The search for more food within these marginal habitats forced foragers to diversify the types of food sources harvested, broadening the subsistence base outward to include more fish, small game, waterfowl, invertebrates (such as snails and shellfish), as well as previously ignored or marginal plant sources. Most importantly, Flannery argues that the need for more food in these marginal environments led to


id: carbohydrate-insulin-model-20260505-0
file: data/en.wikipedia.org/wiki/Carbohydrate–insulin_model-0.md
category: reference
title: Carbohydrate–insulin model
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Carbohydrate–insulin_model
date_saved: 2026-05-05T09:59:11.063944+00:00
instance: kb-cron
parent: carbohydrate-insulin-model-20260505-0
summary:
The carbohydrate-insulin model (CIM) posits that obesity is caused by excess consumption of carbohydrate, which then disrupts normal insulin metabolism leading to weight gain and weight-related illnesses. It is contrasted with the mainstream energy balance model (EBM), which holds that obesity is caused by an excess in calorie consumption compared to calorie expenditure. According to the carbohydrate–insulin model, low-carbohydrate diets would be the most effective in causing long-term weight loss. Notable proponents of the carbohydrate–insulin model include Gary Taubes and David Ludwig. The CIM has been tested in mice and humans. Although some experts consider that these studies falsified the CIM, proponents disagree. Available evidence does not support the existence of a long-term advantage in weight loss for low-carbohydrate diets. == See also == Adipose tissue Appetite Basal metabolic rate Energy homeostasis Glucagon Glycemic index Glycemic load Hyperinsulinemia Insulin sensitivity Insulin Ketogenic diet Leptin Lipogenesis Low-carbohydrate diet Low-glycemic index diet Metabolic Syndrome Obesity Refined carbohydrates Set point theory Sugar Ultra-processed food == References ==


id: coastal-migration-americas-20260505-0
file: data/en.wikipedia.org/wiki/Coastal_migration_(Americas)-0.md
category: reference
title: Coastal migration (Americas)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Coastal_migration_(Americas)
date_saved: 2026-05-05T09:59:13.444822+00:00
instance: kb-cron
parent: coastal-migration-americas-20260505-0
summary:
The coastal migration hypothesis is one of two leading hypotheses about the settlement of the Americas at the time of the Last Glacial Maximum. It proposes one or more migration routes involving watercraft, via the Kurile island chain, along the coast of Beringia and the archipelagos off the Alaskan-British Columbian coast, continuing down the coast to Central and South America. The alternative is the hypothesis solely by interior routes, which assumes migration along an ice-free corridor between the Laurentide and Cordilleran ice sheets during the Last Glacial Maximum.The coastal migration hypothesis has been bolstered by findings such as the report that the sediments in the Port Eliza caves on Vancouver Island indicate the possibility of a survivable climate as far back 16 ka (16,000 years) in the area, while the continental ice sheets were nearing their maximum extent. Despite such research, the hypothesis is still subject to considerable debate. Carlson, Erlandson, and others have argued for a coastal migration from Alaska to the Pacific Northwest pre-11ka (before ≈13,000 calendar years ago) that predates the hypothesized migration of Clovis people moving south through an ice-free corridor located near the continental divide. The coastal migrants may have been followed by the Clovis


id: coastal-migration-americas-20260505-1
file: data/en.wikipedia.org/wiki/Coastal_migration_(Americas)-1.md
category: reference
title: Coastal migration (Americas)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Coastal_migration_(Americas)
date_saved: 2026-05-05T09:59:13.444822+00:00
instance: kb-cron
parent: coastal-migration-americas-20260505-0
summary:
=== Three-wave model === The Three-wave model is an older model that attempts to explain the peopling of the Americas suggested by Greenberg et al. (1986). Using linguistic and genetic data as well as dental anthropology, Greenberg et al. subdivided Native Americans into three groups: Amerind, Na-Dene, and Aleut-Inuit. They explained the linguistic, anatomical, and genetic differences they found in each group as a result of separate migrations or waves out of Northeast Asia to the Americas. This model has been criticized by anthropologist Emőke J.E. Szathmáry who thought that Greenberg's study overstated biological difference. Szathmáry argued that the differences between each group could be better explained by isolation rather than the three migrations. In 1977, Bonatto and Szathámry (1997) concluded that the presence of glaciers isolated the populations from one another, causing them to settle in Beringia rather than use it as a bridge or corridor for migration to mid-latitude America. Bonatto and Szathmáry suggest that after the LGM, humans actually migrated out of Beringia rather than out of Asia. === Beringian "Standstill" hypothesis === The Beringian "Standstill" Hypothesis proposed by Tamm et al. (2007) builds on Bonatto and Szathmáry's idea of migration out of Beringia after the LGM.


id: coastal-migration-americas-20260505-2
file: data/en.wikipedia.org/wiki/Coastal_migration_(Americas)-2.md
category: reference
title: Coastal migration (Americas)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Coastal_migration_(Americas)
date_saved: 2026-05-05T09:59:13.444822+00:00
instance: kb-cron
parent: coastal-migration-americas-20260505-0
summary:
=== Watercraft === Fedje and Christensen (1999:648) also argue that the coast was likely colonized before 13 ka, largely based on watercraft evidence from Japan before 13 ka. Dietary evidence from middens in Indonesia indicates the development of offshore fishing, requiring watercraft, between 35 and 40 ka. Sea-going cultures were mobile in the island-rich environment off the late Pleistocene coast of east Asia, facilitating the spread of marine technology and skills through the Philippines, up the Ryukyu chain, to Japan. Warming of the climate after about 16 ka (although glaciation would remain) could have provided an impetus for seaborne migration up the Kurile island chain towards North America, through some combination of a more hospitable climate and increased ocean productivity. Although no boats have been recovered from early Pacific Coast archaeological sites, this may be due to poor preservation of organic materials and the inundation of coastal areas mentioned above. We can still infer water travel based on the presence of artifacts made by humans found at island sites. Anecdotal evidence comes from the surviving Bella Bella oral tradition, as recorded by Franz Boas in 1898. "In the beginning there was nothing but water and ice and a narrow strip


id: compression-of-morbidity-20260505-0
file: data/en.wikipedia.org/wiki/Compression_of_morbidity-0.md
category: reference
title: Compression of morbidity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Compression_of_morbidity
date_saved: 2026-05-05T09:59:14.618203+00:00
instance: kb-cron
parent: compression-of-morbidity-20260505-0
summary:
The compression of morbidity in public health is a hypothesis put forth by James Fries, professor of medicine at Stanford University School of Medicine. The hypothesis was supported by a 1998 study of 1700 University of Pennsylvania alumni over a period of 20 years. Fries' hypothesis is that the burden of lifetime illness may be compressed into a shorter period before the time of death, if the age of onset of the first chronic infirmity can be postponed. This hypothesis contrasts to the view that as the age of countries' populations tends to increase over time, they will become increasingly infirm and consume an ever-larger proportion of the national budget in healthcare costs. Fries posited that if the hypothesis is confirmed, healthcare costs and patient health overall will be improved. In order to confirm this hypothesis, the evidence must show that it is possible to delay the onset of infirmity, and that corresponding increases in longevity will at least be modest. The evidence is at best mixed. Vincent Mor's "The Compression of Morbidity Hypothesis: A Review of Research and Prospects for the Future" argues that "Cross-national evidence for the validity of the compression of morbidity hypothesis originally proposed by Fries


id: continuum-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Continuum_hypothesis-0.md
category: reference
title: Continuum hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Continuum_hypothesis
date_saved: 2026-05-05T09:59:15.765779+00:00
instance: kb-cron
parent: continuum-hypothesis-20260505-0
summary:
In mathematics, specifically set theory, the continuum hypothesis (abbreviated CH) is a hypothesis about the possible sizes of infinite sets. It states: There is no set whose cardinality is strictly between that of the integers and the real numbers. The name of the hypothesis comes from the term continuum for the real numbers. In Zermelo–Fraenkel set theory with the axiom of choice (ZFC), this is equivalent to the following equation in aleph numbers: 2 ℵ 0 = ℵ 1 {\displaystyle 2^{\aleph _{0}}=\aleph _{1}} , or even shorter with beth numbers: ℶ 1 = ℵ 1 {\displaystyle \beth _{1}=\aleph _{1}} . The continuum hypothesis was advanced by Georg Cantor in 1878. It became one of the most studied problems in set theory, and establishing its truth or falsehood was the first of Hilbert's 23 problems presented in 1900. The answer to this problem is independent of ZFC. This means the axioms of ZFC can neither prove nor disprove the continuum hypothesis, meaning either the continuum hypothesis or its negation can be added as an axiom to ZFC set theory, with the resulting theory being consistent if and only if ZFC is consistent. This independence was proved in 1963 by Paul Cohen,


id: continuum-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Continuum_hypothesis-1.md
category: reference
title: Continuum hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Continuum_hypothesis
date_saved: 2026-05-05T09:59:15.765779+00:00
instance: kb-cron
parent: continuum-hypothesis-20260505-0
summary:
Two sets are said to have the same cardinality or cardinal number if there exists a bijection (a one-to-one correspondence) between them. Intuitively, for two sets S {\displaystyle S} and T {\displaystyle T} to have the same cardinality means that it is possible to "pair off" elements of S {\displaystyle S} with elements of T {\displaystyle T} in such a fashion that every element of S {\displaystyle S} is paired off with exactly one element of T {\displaystyle T} and vice versa. Hence, the set { banana , apple , pear } {\displaystyle \{{\text{banana}},{\text{apple}},{\text{pear}}\}} has the same cardinality as { yellow , red , green } {\displaystyle \{{\text{yellow}},{\text{red}},{\text{green}}\}} despite the sets themselves containing different elements. With infinite sets such as the set of integers or rational numbers, the existence of a bijection between two sets becomes more difficult to demonstrate. The rational numbers Q {\displaystyle \mathbb {Q} } seemingly form a counterexample to the continuum hypothesis: the integers form a proper subset of the rationals, which themselves form a proper subset of the reals, so intuitively, there are more rational numbers than integers and more real numbers than rational numbers. However, this intuitive analysis is flawed since it does not


id: continuum-hypothesis-20260505-2
file: data/en.wikipedia.org/wiki/Continuum_hypothesis-2.md
category: reference
title: Continuum hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Continuum_hypothesis
date_saved: 2026-05-05T09:59:15.765779+00:00
instance: kb-cron
parent: continuum-hypothesis-20260505-0
summary:
== Independence from ZFC == The independence of the continuum hypothesis (CH) from Zermelo–Fraenkel set theory (ZF) follows from combined work of Kurt Gödel and Paul Cohen. Gödel showed that CH cannot be disproved from ZF, even if the axiom of choice (AC) is adopted, i.e. from ZFC. Gödel's proof shows that both CH and AC hold in the constructible universe L {\displaystyle L} , an inner model of ZF set theory, assuming only the axioms of ZF. The existence of an inner model of ZF in which additional axioms hold shows that the additional axioms are (relatively) consistent with ZF, provided ZF itself is consistent. The latter condition cannot be proved in ZF itself, due to Gödel's incompleteness theorems, but is widely believed to be true and can be proved in stronger set theories. Cohen showed that CH cannot be proven from the ZFC axioms, completing the overall independence proof. To prove his result, Cohen developed the method of forcing, which has become a standard tool in set theory. Essentially, this method begins with a model of ZF in which CH holds and constructs another model which contains more sets than the original in a way that CH does


id: continuum-hypothesis-20260505-3
file: data/en.wikipedia.org/wiki/Continuum_hypothesis-3.md
category: reference
title: Continuum hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Continuum_hypothesis
date_saved: 2026-05-05T09:59:15.765779+00:00
instance: kb-cron
parent: continuum-hypothesis-20260505-0
summary:
== Arguments for and against the continuum hypothesis == Gödel believed that CH is false, and that his proof that CH is consistent with ZFC only shows that the Zermelo–Fraenkel axioms do not adequately characterize the universe of sets. Gödel was a Platonist and therefore had no problems with asserting the truth and falsehood of statements independent of their provability. Cohen, though a formalist, also tended towards rejecting CH. Historically, mathematicians who favored a "rich" and "large" universe of sets were against CH, while those favoring a "neat" and "controllable" universe favored CH. Parallel arguments were made for and against the axiom of constructibility, which implies CH. More recently, Matthew Foreman has pointed out that ontological maximalism can actually be used to argue in favor of CH, because among models that have the same reals, models with "more" sets of reals have a better chance of satisfying CH. Another viewpoint is that the conception of set is not specific enough to determine whether CH is true or false. This viewpoint was advanced as early as 1923 by Skolem, even before Gödel's first incompleteness theorem. Skolem argued on the basis of what is now known as Skolem's paradox, and it was


id: continuum-hypothesis-20260505-4
file: data/en.wikipedia.org/wiki/Continuum_hypothesis-4.md
category: reference
title: Continuum hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Continuum_hypothesis
date_saved: 2026-05-05T09:59:15.765779+00:00
instance: kb-cron
parent: continuum-hypothesis-20260505-0
summary:
(occasionally called Cantor's aleph hypothesis). The beth numbers provide an alternative notation for this condition: ℵ α = ℶ α {\displaystyle \aleph _{\alpha }=\beth _{\alpha }} for every ordinal α {\displaystyle \alpha } . The continuum hypothesis is the special case for the ordinal α = 1 {\displaystyle \alpha =1} . GCH was first suggested by Philip Jourdain. For the early history of GCH, see Moore. Like CH, GCH is also independent of ZFC, but Sierpiński proved that ZF + GCH implies the axiom of choice (AC) (and therefore the negation of the axiom of determinacy, AD), so choice and GCH are not independent in ZF; there are no models of ZF in which GCH holds and AC fails. To prove this, Sierpiński showed GCH implies that every cardinality n is smaller than some aleph number, and thus can be ordered. This is done by showing that n is smaller than 2 ℵ 0 + n {\displaystyle 2^{\aleph _{0}+n}} which is smaller than its own Hartogs number—this uses the equality 2 ℵ 0 + n = 2 ⋅ 2 ℵ 0 + n {\displaystyle 2^{\aleph _{0}+n}\,=\,2\cdot \,2^{\aleph _{0}+n}} ; for the full proof, see Gillman. Kurt Gödel showed that GCH


id: cosmic-censorship-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Cosmic_censorship_hypothesis-0.md
category: reference
title: Cosmic censorship hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cosmic_censorship_hypothesis
date_saved: 2026-05-05T09:59:16.959067+00:00
instance: kb-cron
parent: cosmic-censorship-hypothesis-20260505-0
summary:
The weak and the strong cosmic censorship hypotheses are two mathematical conjectures about the structure of gravitational singularities in the context of general relativity. Singularities that arise in the solutions of Einstein's equations are typically hidden within event horizons, and therefore cannot be observed from the rest of spacetime. Singularities that are not so hidden are called naked. The weak cosmic censorship hypothesis was conceived by Roger Penrose in 1969 and posits that no naked singularities is visible from infinity (namely, it is “dressed” by an event horizon) while the strong cosmic censorship hypothesis asserts that generically, general relativity must be a deterministic theory and, thus, our universe must be globally hyperbolic. == Basics == Since the physical behavior of singularities is unknown, if singularities can be observed from the rest of spacetime, causality may break down, and physics may lose its predictive power. The issue cannot be avoided, since according to the Penrose–Hawking singularity theorems, singularities are inevitable in physically reasonable situations. Still, in the absence of naked singularities, the universe, as described by the general theory of relativity, is deterministic: it is possible to predict the entire evolution of the universe (possibly excluding some finite regions of space


id: cosmic-censorship-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Cosmic_censorship_hypothesis-1.md
category: reference
title: Cosmic censorship hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Cosmic_censorship_hypothesis
date_saved: 2026-05-05T09:59:16.959067+00:00
instance: kb-cron
parent: cosmic-censorship-hypothesis-20260505-0
summary:
There are technical difficulties with properly formalizing the notion of a singularity. It is not difficult to construct spacetimes which have naked singularities, but which are not "physically reasonable"; the canonical example of such a spacetime is perhaps the "superextremal" M < | Q | {\displaystyle M<|Q|} Reissner–Nordström solution, which contains a singularity at r = 0 {\displaystyle r=0} that is not surrounded by a horizon. A formal statement needs some set of hypotheses which exclude these situations. Caustics may occur in simple models of gravitational collapse, and can appear to lead to singularities. These have more to do with the simplified models of bulk matter used, and in any case have nothing to do with general relativity, and need to be excluded. Computer models of gravitational collapse have shown that naked singularities can arise, but these models rely on very special circumstances (such as spherical symmetry). These special circumstances need to be excluded by some hypotheses. In 1991, John Preskill and Kip Thorne bet against Stephen Hawking that the hypothesis was false. Hawking conceded the bet in 1997, due to the discovery of the special situations just mentioned, which he characterized as "technicalities". Hawking later reformulated the bet to


id: dark-forest-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Dark_forest_hypothesis-0.md
category: reference
title: Dark forest hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Dark_forest_hypothesis
date_saved: 2026-05-05T09:59:18.155821+00:00
instance: kb-cron
parent: dark-forest-hypothesis-20260505-0
summary:
The dark forest hypothesis is the idea that extraterrestrial civilizations may exist in abundance across the universe, but remain silent and hidden out of fear that revealing themselves would lead to destruction by a more technologically advanced and hostile civilization. It is one of several proposed explanations of the Fermi paradox, which contrasts the apparently high probability of extraterrestrial life with the lack of evidence for it. The hypothesis derives its name from Liu Cixin's 2008 novel The Dark Forest although similar concepts predate the work. == Relation to the Fermi paradox == There is currently no known reliable or reproducible evidence that extraterrestrial life forms have visited or attempted to contact Earth. Despite systematic searches, no transmission and no firm evidence of intelligent extraterrestrial life has been detected. This runs counter to the general observations that: The universe is filled with a very large number of planets, some of which might possess conditions hospitable for life; Terrestrial life is observed to expand until it fills all niches suited to it. These contradictory facts form the basis for the Fermi paradox. == Concept == The "dark forest" hypothesis presumes that any space-faring civilization would view any other intelligent life such


id: documentary-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Documentary_hypothesis-0.md
category: reference
title: Documentary hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Documentary_hypothesis
date_saved: 2026-05-05T09:59:19.356229+00:00
instance: kb-cron
parent: documentary-hypothesis-20260505-0
summary:
The documentary hypothesis (DH) is one of the models used by biblical scholars to explain the origins and composition of the Torah (or Pentateuch, the first five books of the Bible: Genesis, Exodus, Leviticus, Numbers, and Deuteronomy). A version of the documentary hypothesis, frequently identified with the German scholar Julius Wellhausen, was almost universally accepted for most of the 20th century. It posited that the Pentateuch is a compilation of four originally independent documents: the Jahwist, Elohist, Deuteronomist, and Priestly sources, frequently referred to by their initials. The first of these, J, was dated to the Solomonic period (c. 950 BCE). E was dated somewhat later, in the 9th century BCE, and D was dated just before the reign of King Josiah, in the 7th or 8th century BCE. Finally, P was generally dated to the time of Ezra in the 5th century BCE. The sources would have been joined at various points in time by a series of editors or "redactors". The consensus around the classical documentary hypothesis has now faltered. This was triggered in large part by the influential publications of John Van Seters, Hans Heinrich Schmid, and Rolf Rendtorff in the mid-1970s, who argued that J was


id: documentary-hypothesis-20260505-1
file: data/en.wikipedia.org/wiki/Documentary_hypothesis-1.md
category: reference
title: Documentary hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Documentary_hypothesis
date_saved: 2026-05-05T09:59:19.356229+00:00
instance: kb-cron
parent: documentary-hypothesis-20260505-0
summary:
In 1878, Julius Wellhausen published Geschichte Israels, Bd 1 ('History of Israel, Vol 1'). The second edition was printed as Prolegomena zur Geschichte Israels ("Prolegomena to the History of Israel") in 1883, and the work is better known under that name. (The second volume, a synthetic history titled Israelitische und jüdische Geschichte ['Israelite and Jewish History'], did not appear until 1894 and remains untranslated.) Crucially, this historical portrait was based upon two earlier works of his technical analysis: "Die Composition des Hexateuchs" ('The Composition of the Hexateuch') of 1876–77, and sections on the "historical books" (Judges–Kings) in his 1878 edition of Friedrich Bleek's Einleitung in das Alte Testament ('Introduction to the Old Testament'). Wellhausen's documentary hypothesis owed little to Wellhausen himself but was mainly the work of Hupfeld, Eduard Eugène Reuss, Graf, and others, who in turn had built on earlier scholarship. Wellhausen accepted Hupfeld's four sources and, in agreement with Graf, placed the Priestly work last. J was the earliest document, a product of the 10th century BCE and the court of Solomon; E was from the 9th century BCE in the northern Kingdom of Israel, and had been combined by a redactor (editor) with J to form a


id: drift-barrier-hypothesis-20260505-0
file: data/en.wikipedia.org/wiki/Drift-barrier_hypothesis-0.md
category: reference
title: Drift-barrier hypothesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Drift-barrier_hypothesis
date_saved: 2026-05-05T09:59:20.493031+00:00
instance: kb-cron
parent: drift-barrier-hypothesis-20260505-0
summary:
The drift-barrier hypothesis is an evolutionary hypothesis formulated by Michael Lynch in 2010. It suggests that the perfection of the performance of a trait, in a specific environment, by natural selection will hit a hypothetical barrier. The closer a trait comes to perfection, the smaller the fitness advantages become. Once this barrier is reached, the effects of further beneficial mutations are unlikely to be large enough to overcome the power of random genetic drift. Selection generally favors lower mutation rates due to the associated load of deleterious mutations that come with a high mutation rate. == Description == Every population contains a certain amount of genetic variation, coding for different functional traits. When the environment in which the population lives changes, some of these traits turn out to be more advantageous for this new situation than others. Through natural selection and random genetic drift, the traits with a negative effect on population fitness disappear from the gene pool. The balance between the influence of natural selection and genetic drift on the population mutation rate is mainly determined by the population size. Large populations are predicted to generally have lower mutation rates than smaller populations. Populations containing individuals with high mutation


id: duhem-quine-thesis-20260505-0
file: data/en.wikipedia.org/wiki/Duhem–Quine_thesis-0.md
category: reference
title: Duhem–Quine thesis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Duhem–Quine_thesis
date_saved: 2026-05-05T09:59:21.675514+00:00
instance: kb-cron
parent: duhem-quine-thesis-20260505-0
summary:
In philosophy of science, the Duhem–Quine thesis, also called the Duhem–Quine problem, says that unambiguous falsifications of a scientific hypothesis are impossible, because an empirical test of the hypothesis requires one or more background assumptions. Rather than disproving the main hypothesis, the blame can be placed on one of the background beliefs or "auxiliary" hypotheses. It is named after French theoretical physicist Pierre Duhem and American logician Willard Van Orman Quine, who wrote about similar concepts. In recent decades, the set of associated assumptions supporting a thesis sometimes is called a bundle of hypotheses, i.e. a hypothesis and its background assumptions. Although a bundle of hypotheses as a whole can be tested against the empirical world and be falsified if it fails the test, the Duhem–Quine thesis says it is impossible to isolate a single hypothesis in the bundle, a viewpoint called confirmation holism. == Overview == The Duhem–Quine thesis argues that no scientific hypothesis is by itself capable of making predictions. Instead, deriving predictions from the hypothesis typically requires background assumptions that several other hypotheses are correct — that an experiment works as predicted, or that previous scientific theory is accurate. For instance, as evidence against the idea that


