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Record W1975017690 · doi:10.1037/0096-1523.33.2.330

Task-set reconfiguration suspends perceptual processing: Evidence from semantic priming during the attentional blink.

2007· article· en· W1975017690 on OpenAlexafffund
François Vachon, Sébastien Tremblay, Dylan M. Jones

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité Laval
FundersEconomic and Social Research CouncilFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsControl reconfigurationAttentional blinkPriming (agriculture)Task (project management)PerceptionSet (abstract data type)Task switchingRapid serial visual presentationCognitive psychologyPsychologyComputer scienceNeuroscienceCognitionBiology

Abstract

fetched live from OpenAlex

When two visual targets, Target 1 (T1) and Target 2 (T2), are presented among a rapid sequence of distractors, processing of T1 produces an attentional blink. Typically, processing of T2 is markedly impaired, except when T1 and T2 are adjacent (Lag 1 sparing). However, if a shift of task set--a change in task requirements from T1 to T2--occurs, this sparing is reduced substantially. With a semantic priming technique, in which T1 could be either related or unrelated to T2, the priming of T2 by T1 diminished markedly at Lag 1, when the transition between T1 and T2 involved a switch in either location (Experiments 1 and 2) or task (Experiment 3), but remained unaffected at other lags. These results suggest that perceptual processing of T2 cannot be carried out in parallel with task-set reconfiguration.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.226
GPT teacher head0.447
Teacher spread0.222 · 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

Citations24
Published2007
Admission routes2
Has abstractyes

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