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Record W2098240276 · doi:10.1177/0956797613516147

Catching Eyes

2014· article· en· W2098240276 on OpenAlex
Anne Böckler, Robrecht P. R. D. van der Wel, Timothy N. Welsh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePsychological Science · 2014
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaAssociation for Psychological Science
KeywordsGazePsychologyEye contactEye movementMotion (physics)Cognitive psychologyCommunicationSensory cueNeuroscienceComputer visionComputer science

Abstract

fetched live from OpenAlex

Direct eye contact and motion onset are two powerful cues that capture attention. In the present study, we combined direct gaze with the sudden onset of motion to determine whether these cues have independent or shared influences. Participants identified targets presented randomly on one of four faces. Initially, two faces depicted direct gaze, and two faces depicted averted gaze. Simultaneously with or 900 ms before target presentation, one face with averted gaze switched to direct gaze, and one face with direct gaze switched to averted gaze. When gaze transitions and target presentation were simultaneous, the greatest response-time facilitation occurred at the location of the sudden onset of direct gaze. When target presentation was delayed, direct-gaze cues maintained a facilitatory influence, whereas motion cues induced an inhibitory influence. These findings reveal that gaze cues and motion cues at the same location influence information processing via independent and concurrently acting social and nonsocial attention channels.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.586
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.100
GPT teacher head0.407
Teacher spread0.307 · 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