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Record W4292767223 · doi:10.31234/osf.io/q4dpg

Emphasizing temporal and semantic associations from encoding affects free recall at retrieval

2022· preprint· en· W4292767223 on OpenAlexafffund
Bryan Hong, Carleigh Pace-Tonna, Morgan D. Barense, Michael L. Mack

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaFondation Brain Canada
KeywordsRecallFree recallEncoding (memory)Context-dependent memoryCognitive psychologySemantic memoryPeriod (music)Recall testPsychologyEncoding specificity principleCluster analysisEpisodic memoryComputer scienceArtificial intelligenceCognition

Abstract

fetched live from OpenAlex

Paradigms using the free recall of word lists have furthered our understanding of the organizational structure of memory by elucidating the role of contextual associations on memory search. These studies have provided evidence supporting the relationship between the strength of contextual reinstatement and overall memory performance at recall. In the current study, we adapted the traditional word list-learning paradigm to investigate whether emphasizing certain contextual associations between list items would influence subsequent retrieval. Specifically, we introduced a review period between the initial encoding and recall of word lists where items were repeated in an order that highlighted either the temporal or semantic associations at encoding. We found that a temporal review period led to stronger temporal clustering compared to a semantic or a random baseline review period, and a semantic review period led to stronger semantic clustering compared to a temporal or random baseline review period. Moreover, participants recalled more list items when semantic associations were emphasized, with the degree of clustering at recall predicting memory performance. These results demonstrate that emphasizing contextual associations during a review period after initial encoding can affect subsequent memory organization and recall.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.003
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 head0.073
GPT teacher head0.311
Teacher spread0.238 · 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

Citations4
Published2022
Admission routes2
Has abstractyes

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