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Record W2554387362 · doi:10.1037/xhp0000326

Much ado about nothing: Capturing attention toward locations without new perceptual events.

2016· article· en· W2554387362 on OpenAlexafffund
Matthew D. Hilchey, J. Eric T. Taylor, Jay Pratt

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2016
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaKillam Trusts
KeywordsStimulus (psychology)SalientSingletonPerceptionLuminanceCognitive psychologyTop-down and bottom-up designComputer scienceVisual perceptionVisual attentionVisual searchPsychologyCommunicationArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Popular frameworks of attention propose that visual orienting occurs through a combination of bottom-up (stimulus-driven) and top-down (goal-directed) processes. Much of the basic research on these processes adheres paradigmatically to experimental methods that introduce salient but task-irrelevant stimuli (objects or transients) to the visual environment to determine whether attention is captured to their locations. This common practice of changing or adding a stimulus to a location to determine whether it captures attention reflects a notion that locations at which new features or stimuli spontaneously appear are prioritized above all else. In this article, we challenge this notion with results from a modified additional singleton paradigm. In the critical condition, following a preview array of placeholder stimuli, 1 placeholder stimulus transforms into a target diamond and changes luminance at the same time that all other placeholders, except 1 (the truly "static singleton") change in luminance. This static singleton location, which involves neither a new stimulus nor any sensory transient, produces a clear pattern of attentional capture originating near its location. These findings violate multiple bottom-up and top-down perspectives while encouraging a new approach to studying attentional capture. (PsycINFO Database Record

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.446
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.112
GPT teacher head0.402
Teacher spread0.290 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2016
Admission routes2
Has abstractyes

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