Revisiting the role of visual working memory in attentional control settings
Bibliographic record
Abstract
Observers adopt attentional control setting (ACS) based on their goals; stimuli that match the current goal will capture attention, whereas stimuli that do not match the current goal will not. In the present study, we revisited the role of VWM in maintaining ACSs capable of guiding attentional capture. Participants completed a Posner cueing task while either remembering a colour (Experiments 1a/1b) or searching for a colour (Experiments 2/3). To encourage the use of VWM, the colour changed on each trial. Results indicate that merely remembering a colour using VWM did not prevent memory non-matching colours from capturing attention (Experiments 1a/1b). Conversely, when participants searched for one colour, VWM supported an ACS that eliminated capture by non-matching colours (Experiments 2/3), though not if participants searched for two colours (Experiment 3). We conclude that VWM can maintain an ACS of one searched-for item that is capable of guiding attentional capture.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".