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Record W2002992816 · doi:10.1037/a0014258

Linear changes in the spatial extent of the focus of attention across time.

2009· article· en· W2002992816 on OpenAlexafffund
Lisa N. Jefferies, Vincent Di Lollo

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStimulus onset asynchronyAttentional blinkLagFocus (optics)PerceptionConverseAsynchrony (computer programming)STREAMSStimulus (psychology)PsychologyCognitive psychologyComputer scienceMathematicsNeuroscienceOpticsPhysicsGeometryTelecommunications

Abstract

fetched live from OpenAlex

This research examined changes in the spatial extent of focal attention over time. The Attentional Blink (impaired perception of the second of two targets) and Lag-1 sparing (the seemingly paradoxical finding that second-target accuracy is high when the second target immediately follows the first) were employed in a dual-stream paradigm to index spatiotemporal changes in focal attention. Lag-1 sparing occurs to targets in different streams if the second target falls within the focus of attention. Focal attention is assumed to initially encompass both streams but to shrink rapidly to the first-target stream, thus withdrawing from the second target if it appears in the opposite stream. The time available for the focus to shrink before second target onset was manipulated by varying the stimulus-onset asynchrony (SOA) between successive items in the stream. There was a progressive transition from Lag-1 sparing to its converse (Lag-1 deficit) as the SOA was increased. This transition was related linearly to SOA, which suggests that the spatial extent of focal attention varies linearly over time.

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 score0.652
Threshold uncertainty score0.339

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.114
GPT teacher head0.435
Teacher spread0.320 · 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

Citations42
Published2009
Admission routes2
Has abstractyes

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