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Record W4214552879 · doi:10.1080/13506285.2022.2044949

Revisiting the role of visual working memory in attentional control settings

2022· article· en· W4214552879 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueVisual Cognition · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPsychologyCognitive psychologyWorking memoryTask (project management)Attentional controlControl (management)Matching (statistics)Visual searchCognitionNeuroscienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

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.

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.

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 score0.145
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.072
GPT teacher head0.365
Teacher spread0.293 · 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