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Record W2013026681 · doi:10.1101/lm.96305

A latent cue preference based on sodium depletion in rats

2005· article· en· W2013026681 on OpenAlexaff
Eric M. Stouffer, Norman M. White

Bibliographic record

VenueLearning & Memory · 2005
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcGill University
Fundersnot available
KeywordsPreferenceCompartment (ship)PsychologySodiumConditioningSalt solutionChemistryTasteConditioned place preferenceAvoidance learningSalt (chemistry)NeuroscienceStatistics

Abstract

fetched live from OpenAlex

Three experiments show latent (or incidental) learning of salt-cue relationships using a conditioned cue-preference paradigm. Rats drank a salt solution while confined in one compartment and water in an adjacent, distinct compartment on alternate days. When given access to the two compartments with no solutions present, sodium-deprived rats preferred their salt-paired compartments; normal rats preferred their water-paired compartments. Reversing the deprivation states of the two groups reversed their preferences. These results show that rats can latently acquire associations between environmental cues and the taste of salt, and can use this information flexibly to guide behavior based upon internal cues produced by sodium deprivation.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.315
Teacher spread0.261 · 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

Citations20
Published2005
Admission routes1
Has abstractyes

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