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Record W2804965507 · doi:10.1037/abn0000361

Looking at the eyes interferes with facial emotion recognition in alexithymia.

2018· article· en· W2804965507 on OpenAlexafffundabout
Esther Fujiwara

Bibliographic record

VenueJournal of Abnormal Psychology · 2018
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates - Health Solutions
KeywordsAlexithymiaPsychologyToronto Alexithymia ScaleFacial expressionAutism spectrum disorderPsycINFOMoodFeelingAnxietyPersonalitySocial anxietyDevelopmental psychologyAutismClinical psychologyCognitive psychologyPsychiatrySocial psychologyCommunicationMEDLINE

Abstract

fetched live from OpenAlex

= 76) were enrolled in this study. Participants judged the mixture ratio of emotional expressions while their eye movements were recorded. Controlling for group differences in mood and anxiety, HA showed similar accuracy but a reduced viewing preference of facial eye regions compared to LA (p = .02). More attention to the eye regions was related to lower accuracy in HA (p = .02) but to slightly higher accuracy in LA (p = .07). The current findings point to a role of alexithymia in attentional avoidance of other people's eyes, similar to previous findings in autism spectrum disorder. Eye contact may be perceived as a greater emotional challenge by those with alexithymia, disrupting downstream processing of facial emotions. (PsycINFO Database Record

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.460

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.323
Teacher spread0.296 · 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 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

Citations38
Published2018
Admission routes3
Has abstractyes

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