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Record W2018213637 · doi:10.1068/p3089

The Role of Attention in Temporal Integration

2001· article· en· W2018213637 on OpenAlexaff
Troy A. W. Visser, James T. Enns

Bibliographic record

VenuePerception · 2001
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPerceptStimulus (psychology)Cognitive psychologyPsychologyVisual maskingVisual attentionAttentional blinkVisual perceptionStimulus onset asynchronyPerceptionNeuroscience

Abstract

fetched live from OpenAlex

When two visual patterns are presented in rapid succession, their contours may be combined into a single unified percept. This temporal integration is known to be influenced by such low-level visual factors as stimulus intensity, contour proximity, and stimulus duration. In this study we asked whether temporal integration is modulated by an attentional-blink procedure. The results from a localisation task in experiment 1 and a detection task in experiment 2 pointed to two separate effects. First, greater attentional availability increased the accuracy of spatial localisation. Second, it increased the duration over which successive stimuli could be integrated. These results imply that theories of visible persistence and visual masking must account for attentional influences in addition to lower-level effects. They also have practical implications for use of the temporal-integration task in the assessment of group and individual differences.

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)0.010
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.000
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 head0.046
GPT teacher head0.325
Teacher spread0.280 · 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

Citations56
Published2001
Admission routes1
Has abstractyes

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