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Record W1598735593 · doi:10.1002/acp.3053

The Delay Before Recall Changes the Remembered Duration of 15‐minute Video Sequences

2014· article· en· W1598735593 on OpenAlexaff
Simon Grondin, Vincent Laflamme, Nicolas Bisson, Félix Désautels

Bibliographic record

VenueApplied Cognitive Psychology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSadnessRecallDuration (music)PsychologyAudiologyTime perceptionCognitionDevelopmental psychologyCognitive psychologySocial psychologyPsychiatryMedicineAnger

Abstract

fetched live from OpenAlex

Summary The aim of this study was to determine if the passage of time changes the memory of the duration of joyful or sad events. Participants were asked to look at a series of brief videos lasting 15 minutes and to estimate retrospectively and verbally (with chronometric units) the duration of this 15‐minute period. There were two independent variables: the emotion conditions (joy, sadness and neutral) and the recall conditions (immediately after the presentation of videos, 1 week later or 1 month later). The results show that the estimated time is largely overestimated in the 1‐week and 1‐month condition but not when the recall is immediate. This effect applies to each emotional condition, but there was no significant difference between the emotion conditions. The effect of emotion on the estimation of long intervals judged retrospectively seems minimal in comparison with the cognitive effect associated with the passage of time. Copyright © 2014 John Wiley & Sons, Ltd.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.324
Teacher spread0.274 · 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 designObservational
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

Citations17
Published2014
Admission routes1
Has abstractyes

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