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Record W4414873882 · doi:10.1037/xge0001850

Prospective and retrospective awareness of moment-to-moment fluctuations in visual working memory performance.

2025· article· en· W4414873882 on OpenAlexafffund
Olga Kozlova, Kirsten Adam, Keisuke Fukuda

Bibliographic record

VenueJournal of Experimental Psychology General · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsProspective memoryMetacognitionWorking memoryRetrospective memoryAffect (linguistics)Task (project management)Prospective cohort studyMetamemory

Abstract

fetched live from OpenAlex

= 85), we demonstrate that retrospective awareness is more sensitive to VWM performance fluctuations than prospective awareness in young adults, though both metacognitive abilities are imperfect. Poor metacognitive abilities reflected a general tendency-particularly among low VWM capacity individuals-to overestimate upcoming VWM performance. When individuals overestimated their upcoming VWM performance (i.e., prospective failures), VWM performance significantly reduced compared to the preceding trials of a prospective failure. Moreover, this reduction in performance significantly lingered into subsequent trials. However, individuals' prospective and retrospective awareness better aligned to VWM performance after a prospective failure. This postfailure calibration occurred even without feedback signaling a prospective failure (Experiment 2), suggesting a metacognitive efficiency in recognizing the initial overestimation. Taken together, our results suggest that individuals, particularly low-capacity individuals, have a limited awareness toward upcoming VWM performance but exhibit metacognitive adjustments immediately following a prospective failure. (PsycInfo Database Record (c) 2025 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)0.000
metaresearch head score (Gemma)0.000
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 score0.220
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.075
GPT teacher head0.433
Teacher spread0.358 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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