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Record W2057226439 · doi:10.1093/chemse/26.8.1015

Determination of Saltiness from the Laws of Thermodynamics--Estimating the Gas Constant from Psychophysical Experiments

2001· article· en· W2057226439 on OpenAlexafffund
Kenneth H. Norwich

Bibliographic record

VenueChemical Senses · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
Topicstochastic dynamics and bifurcation
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermodynamicsEntropy (arrow of time)ChemistrySecond law of thermodynamicsMathematicsLawStatistical physicsPhysics

Abstract

fetched live from OpenAlex

One can relate the saltiness of a solution of a given substance to the concentration of the solution by means of one of the well-known psychophysical laws. One can also compare the saltiness of solutions of different solutes which have the same concentration, since different substances are intrinsically more salty or less salty. We develop here an equation that relates saltiness both to the concentration of the substance (psychophysical) and to a distinguishing physical property of the salt (intrinsic). For a fixed standard molar entropy of the salt being tasted, the equation simplifies to Fechner's law. When one allows for the intrinsic 'noise' in the chemoreceptor, the equation generalizes to include Stevens's law, with corresponding decrease in the threshold for taste. This threshold reduction exemplifies the principle of stochastic resonance. The theory is validated with reference to experimental data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.268
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2001
Admission routes2
Has abstractyes

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