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Record W4280533352 · doi:10.1037/cep0000283

Pupil dilation during recognition reflects the subjective recollection/familiarity experience at test rather than the level of processing at encoding.

2022· article· en· W4280533352 on OpenAlexfundno aff
Alexander Taikh, Glen E. Bodner

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2022
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPupillary responsePsychologyPupilPupillometryRecallRecognition memoryCognitive psychologyTest (biology)Levels-of-processing effectDilation (metric space)Encoding (memory)CognitionNeuroscience

Abstract

fetched live from OpenAlex

have been offered. By a retrieval effort account, the pupil's response on a recognition test reflects the cognitive effort needed to retrieve items from memory. By a memory strength account, pupil dilation reflects the strength of the subjective memory experience elicited by items at test. To compare these accounts, we varied levels of processing (LOP) at study, then measured pupil dilation on a delayed recognition test during which participants made recollection/familiarity judgements. Pupil dilation at test was similar whether test items had been studied in a deep or shallow LOP task, but was greater when deep, shallow, and new test items were experienced as recollected rather than as familiar. This pattern supports the memory strength account rather than the retrieval effort account of pupil dilation during a recognition test. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.174
GPT teacher head0.344
Teacher spread0.170 · 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 teacher head, not a consensus.

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

Citations8
Published2022
Admission routes1
Has abstractyes

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