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Record W2062799943 · doi:10.1037//0097-7403.26.3.340

Mechanisms of second-order conditioning with a backward conditioned stimulus.

2000· article· en· W2062799943 on OpenAlexaff
Douglas A. Williams, Jennifer L. Hurlburt

Bibliographic record

VenueJournal of Experimental Psychology Animal Behavior Processes · 2000
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsMeasures of conditioned emotional responseConditioningClassical conditioningReinforcementUnconditioned stimulusPsychologyStimulus (psychology)Extinction (optical mineralogy)Conditioned responseExcitatory postsynaptic potentialNeutral stimulusCognitive psychologyNeuroscienceInhibitory postsynaptic potentialMathematicsSocial psychologyStatisticsPhysics

Abstract

fetched live from OpenAlex

Five conditioned suppression experiments with rats examined the conditions under which backward pairings endow a first-order conditioned stimulus (CS1) with the ability to serve as a secondary reinforcer. Experiments 2-5B found evidence for excitatory second-order conditioning (SOC) if, during first-order pairings, the US-CS1 interval was 0 s rather than 3 s. Levels of SOC were comparable after forward and backward pairings (Experiments 1-3), and were unaffected by extinction of CS1 after SOC (Experiment 3). These results suggest that forward and backward CS1s support SOC for the same reason, and they call into question the need to invoke any special mechanism such as memory integration.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.070
GPT teacher head0.379
Teacher spread0.309 · 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
Published2000
Admission routes1
Has abstractyes

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