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Record W2344833530 · doi:10.1037/xhp0000058

Contingent capture effects in temporal order judgments.

2015· article· en· W2344833530 on OpenAlexafffund
Sabine Born, Dirk Kerzel, Jay Pratt

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungEuropean Commission
KeywordsPsychologyCognitive psychologySingletonSet (abstract data type)Attentional controlVisual searchVisual attentionAffect (linguistics)Task (project management)PerceptionCognitionCommunicationComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

The contingent attentional capture hypothesis proposes that visual stimuli that do not possess characteristics relevant for the current task will not capture attention, irrespective of their bottom-up saliency. Typically, contingent capture is tested in a spatial cuing paradigm, comparing manual reaction times (RTs) across different conditions. However, attention may act through several mechanisms and RTs may not be ideal to disentangle those different components. In 3 experiments, we examined whether color singleton cues provoke cuing effects in temporal order judgments (TOJs) and whether they would be contingent on attentional control sets. Experiment 1 showed that color singleton cues indeed produce cuing effects in TOJs, even in a cluttered and dynamic target display containing multiple heterogeneous distractors. In Experiment 2, consistent with contingent capture, we observed reliable cuing effects only when the singleton cue matched participants' current attentional control set. Experiment 3 suggests that a sensory interaction account of the differences found in Experiment 2 is unlikely. Our results help to discern the attentional components that may play a role in contingent capture. Further, we discuss a number of other effects (e.g., reversed cuing effects) that are found in RTs, but so far have not been reported in TOJs. Those differences suggest that RTs are influenced by a multitude of mechanisms; however, not all of these mechanisms may affect TOJs. We conclude by highlighting how the study of attentional capture in TOJs provides valuable insights for the attention literature, but also for studies concerned with the perceived timing between stimuli.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.807

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.169
GPT teacher head0.432
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2015
Admission routes2
Has abstractyes

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