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Record W3165689364 · doi:10.1002/acp.3877

How emotion influences the details recalled in autobiographical memory

2021· article· en· W3165689364 on OpenAlexafffund
Victoria Wardell, Christopher R. Madan, Taylyn J. Jameson, Chantelle M. Cocquyt, Katherine J. Checknita, Hallie Liu, Daniela J. Palombo

Bibliographic record

VenueApplied Cognitive Psychology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutobiographical memoryMnemonicPsychologyRecallCognitive psychologyPerceptionChildhood amnesiaEpisodic memoryMemory errorsChildhood memoryCognitionNeuroscience

Abstract

fetched live from OpenAlex

Abstract A wealth of research suggests that emotion enhances memory. Yet, this enhancement is not uniform. While some theories posit that emotion enhances memory for sensory/perceptual information, such an enhancement has not been observed in mnemonic detail production. However, a focus on remote events (often more semanticized) may be masking an effect. Focusing on perceptual details, we examined the effects of emotion on mnemonic detail, sampling both remote and recent autobiographical events. We administered the Autobiographical Interview, a protocol that parses autobiographical details into categories (perceptual, event, emotion/thoughts, place, and time). Participants ( N = 56) recalled memories that were positive, negative, and neutral from recent (≲3 months old) and remote (~1–5 years old) time periods. Recollection of perceptual details did not differ for emotional versus neutral memories at either retention interval. However, emotion affected memory for other detail types, contingent on time period. Our findings enrich our understanding of the nuance of emotional memory.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.216
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.325
Teacher spread0.273 · 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.

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

Citations25
Published2021
Admission routes2
Has abstractyes

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