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Record W4224001819 · doi:10.1037/emo0001076

What’s in a gaze, what’s in a face?: The direct gaze effect can be modulated by emotion expression.

2022· article· en· W4224001819 on OpenAlexfundno aff
Roxana Pittig, Robrecht P. R. D. van der Wel, Timothy N. Welsh, Anne Böckler

Bibliographic record

VenueEmotion · 2022
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft
KeywordsGazePsychologyFacial expressionCognitive psychologyEmotional expressionExpression (computer science)PsycINFOEye trackingNonverbal communicationCommunicationArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Gaze direction and emotion expression are salient facial features that facilitate social interactions. Previous studies addressed how gaze direction influences the evaluation and recognition of emotion expressions, but few have tested how emotion expression influences attentional processing of direct versus averted gaze faces. The present study examined whether the prioritization of direct gaze (toward the observer) relative to averted gaze (away from the observer) is modulated by the emotional expression of the observed face. Participants identified targets presented on the forehead of one of four faces in a 2 × 2 design (gaze direction: direct/averted; motion: sudden/static). Emotion expressions of the faces (neutral, angry, fearful, happy, disgusted) differed across participants. Direct gaze effects emerged-response times were shorter for targets on direct gaze than on averted gaze faces. This direct gaze effect was enhanced in angry faces (approach-oriented) and reduced in fearful faces (avoidance-oriented). "Weaker" approach- and avoidance-oriented expressions (happy and disgusted) did not modulate the direct gaze effect. These findings suggest that the context of facial emotion expressions influences attentional processing. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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)0.001
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.271
Teacher spread0.240 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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