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Record W2595575045

Impaired categorical perception of emotional facial expressions in alexithymia

2016· article· en· W2595575045 on OpenAlexaboutno aff
Delphine Grynberg, Pierre Maurage, Fabien D’Hondt, Sally Olderbak, Olga Pollatos

Bibliographic record

VenueEuropean Health Psychologist · 2016
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyDisgustSadnessFacial expressionHappinessAngerPerceptionEmotional expressionCategorizationToronto Alexithymia ScaleAssociation (psychology)Developmental psychologyCognitive psychologyClinical psychologySocial psychologyCommunicationPsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

Alexithymia is characterized by low awareness of one’s own emotions and by an externally-oriented thinking. It has been linked to social impairments, notably with lower abilities to decode emotional facial expressions (EFE). However, it remained unclear whether alexithymia is associated with a deficit for subtle (i.e., expressed at low intensities) emotions. Forty participants completed the 20-item Toronto Alexithymia Scale and an emotional morphing paradigm which displayed morphed emotions along continua between neutral and full-blown emotions (anger, fear, sadness, disgust, and happiness). Main results showed that high levels of alexithymia, and more particularly externally-oriented thinking, were associated with increased identification threshold for fearful expressions and impaired recognition of low-intensity fearful faces. This study thus supports that alexithymia is characterized by an underestimation of fearful expressions and by altered identification of subtle EFE, which are the most frequently experiences in real-life situations.

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 score0.261
Threshold uncertainty score0.525

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 head0.062
GPT teacher head0.366
Teacher spread0.305 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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