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Record W1977638202 · doi:10.1080/00221300309601169

The CS-Preexposure Effect in Conditioned Taste-Aversion Learning in Golden Hamsters

2003· article· en· W1977638202 on OpenAlexaff
David DiBattista, Laurie Hollis-walker, L. Kathleen Hague

Bibliographic record

VenueThe Journal of General Psychology · 2003
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBrock University
Fundersnot available
KeywordsTaste aversionConditioningClassical conditioningUnconditioned stimulusTasteLithium chlorideSalineStimulus (psychology)PsychologyGolden hamsterEndocrinologyInternal medicineBiologyChemistryNeuroscienceHamsterMedicineCognitive psychologyMathematics

Abstract

fetched live from OpenAlex

In Experiment 1, golden hamsters were injected with either 0.9% saline or the nausea-inducing agent, lithium chloride (LiCL), immediately after consuming a flavored diet that was either novel or familiar. The LiCl-induced aversion was strong in hamsters for which the flavored diet was novel, but no significant aversion was observed in hamsters that were familiar with the flavored diet. In Experiment 2, the strength of the LiCl-induced aversion was related inversely to the amount of conditioned-stimulus (CS) preexposure and directly to the duration of the preexposure-conditioning interval. Thus, although some previous researchers have suggested that hamsters may not demonstrate the CS-preexposure effect in a conditioned taste-aversion paradigm, they clearly did so under the conditions of the present experiments, and moreover, the characteristics of the CS-preexposure effect in hamsters were generally similar to those observed in rats.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.343
Teacher spread0.294 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

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