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Attentional capture by visual singletons is mediated by top‐down task set: New evidence from the N2pc component

2008· article· en· W1995913285 on OpenAlexaff
Mónika Kiss, Pierre Jolicœur, Roberto Dell’Acqua, Martin Eimer

Bibliographic record

VenuePsychophysiology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité de Montréal
FundersBiotechnology and Biological Sciences Research CouncilDirectorate for Biological SciencesWellcome Trust
KeywordsN2pcVisual searchPsychologySingletonStimulus (psychology)SalientCognitive psychologyTask (project management)Set (abstract data type)Top-down and bottom-up designVisual attentionCommunicationCognitionNeuroscienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

To investigate whether attentional capture by salient visual stimuli is mediated by current task sets, we measured the N2pc component as a marker of the spatial locus of visual attention during visual search. In each trial, a singleton stimulus that could either be a target (color task: red circle; shape task: green diamond) or a nontarget (blue circle or green square) was presented among uniform distractors (green circles). As predicted by the view that attentional capture is contingent on task set, the N2pc was strongly affected by task instructions. It was maximal for targets, attenuated but still reliably present for nontarget singletons defined in the target dimension (even when these were accompanied by an irrelevant-dimension singleton), and small or absent for equally salient irrelevant-dimension singletons. Results demonstrate that attentional capture is not a purely bottom-up phenomenon, but is strongly determined by top-down task set.

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)0.000
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.127
GPT teacher head0.365
Teacher spread0.239 · 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

Citations106
Published2008
Admission routes1
Has abstractyes

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