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Record W4285014103 · doi:10.1037/cep0000289

Two dichotomies of recognition memory.

2022· review· en· W4285014103 on OpenAlexfundno aff
William E. Hockley

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2022
Typereview
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDichotomyPsychologyPsycINFOAssociative propertyCognitive psychologyCognitive scienceRecognition memoryEncoding (memory)Psychological researchReconstructive memoryRepresentation (politics)CognitionSemantic memoryExplicit memorySocial psychologyNeuroscienceEpistemology

Abstract

fetched live from OpenAlex

) proposed that recognition decisions could be based on the sense of familiarity engendered by the stimulus or on the retrieval of conceptual, semantic, and contextual information about the target. These two distinctions have motivated a considerable amount of research over the past 40 years and have provided much of the bases for our current understanding of recognition memory. Selective aspects of this research are reviewed to show how theories of recognition memory have developed to embody these two dichotomies. (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 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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.006
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.003

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 head0.199
GPT teacher head0.396
Teacher spread0.197 · 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 designNot applicable
Domainnot available
GenreReview

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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