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Record W2154258060 · doi:10.1101/lm.028183.112

Timing and cue competition in conditioning of the nictitating membrane response of the rabbit (<i>Oryctolagus cuniculus</i>)

2013· article· en· W2154258060 on OpenAlexafffund
E. James Kehoe, Elliot A. Ludvig, Richard S. Sutton

Bibliographic record

VenueLearning & Memory · 2013
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates
KeywordsNictitating membraneConditioningClassical conditioningUnconditioned stimulusPsychologyEyeblink conditioningNeuroscienceStimulus (psychology)AudiologyForebrainChemistryCognitive psychologyCentral nervous systemMedicineMathematicsStatistics

Abstract

fetched live from OpenAlex

Rabbits were classically conditioned using compounds of tone and light conditioned stimuli (CSs) presented with either simultaneous onsets (Experiment 1) or serial onsets (Experiment 2) in a delay conditioning paradigm. Training with the simultaneous compound reduced the likelihood of a conditioned response (CR) to the individual CSs ("mutual overshadowing") but left CR timing unaltered. CR peaks were consistently clustered around the time of unconditioned stimulus (US) delivery. Training with the serial compound (CSA→CSB→US) reduced responding to CSB ("temporal primacy/information effect") but this effect was prevented by prior CSB→US pairings. In both cases, serial compound training altered CR timing. On CSA→CSB test trials, the CRs were accelerated; the CR peaks occurred after CSB onset but well before the time of US delivery. Conversely, CRs on CSB- trials were decelerated; the distribution of CR peaks was variable but centered well after the US. Timing on CSB- trials was at most only slightly accelerated. The results are discussed with respect to processes of generalization and spectral timing applicable to the cerebellar and forebrain pathways in eyeblink preparations.

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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.035
GPT teacher head0.268
Teacher spread0.233 · 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
Published2013
Admission routes2
Has abstractyes

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