Prospective and retrospective awareness of moment-to-moment fluctuations in visual working memory performance.
Bibliographic record
Abstract
= 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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".