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Record W2150984463 · doi:10.1111/1467-9280.00275

Competition-Induced Visual Field Differences in Search

2000· article· en· W2150984463 on OpenAlexaff
Jillian H. Fecteau, James T. Enns, Alan Kingstone

Bibliographic record

VenuePsychological Science · 2000
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVisual searchPsychologyVisual fieldCognitive psychologyStimulus (psychology)N2pcCompetition (biology)Visual perceptionLateralization of brain functionTask (project management)NeurosciencePerception

Abstract

fetched live from OpenAlex

Do visual field effects point to differences in cortical representation, or do they reflect differences in the way these representations are used by other brain regions? This study explored three attributes of visual search that provide strong evidence in favor of differences in use. Competition refers to the finding that visual field differences in search efficiency are larger in whole- than in half-field displays (both left-right and upper-lower half-fields). Task specialization refers to the finding that some tasks favor one hemisphere whereas other tasks favor the other hemisphere, even though the same stimulus displays are used in both tasks. Anatomical alignment refers to the finding that competition effects are altered if the quadrants of the visual display are not aligned with the cortical quadrants of the observer. We propose that visual field specialization in search is the result of a competition involving limited access to cortical visual representations by the extended neural networks of attention.

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 categoriesInsufficient 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 score0.479
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.169
GPT teacher head0.443
Teacher spread0.274 · 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

Citations45
Published2000
Admission routes1
Has abstractyes

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