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Record W2005457886 · doi:10.1159/000288664

Alexithymia and the Recognition of Facial Expressions of Emotion

2010· article· en· W2005457886 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePsychotherapy and Psychosomatics · 2010
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsAlexithymiaPsychologyFacial expressionCategorizationToronto Alexithymia ScaleNonverbal communicationPerceptionEmotion perceptionEmotion recognitionEmotional expressionDevelopmental psychologyClinical psychologyCommunication

Abstract

fetched live from OpenAlex

Slides of photographs depicting posed facial expressions of nine different emotions were presented to 131 females and 85 males who were asked to identify the emotion(s) being experienced by the person in each photograph. Subjects were then administered the 20-item version of the Toronto Alexithymia Scale; the 33rd and 66th percentiles were used to categorize subjects into high, moderate, and low alexithymia groups. Results showed that the high alexithymia group was significantly less able to recognize facial expressions of emotions than the low alexithymia group. There was no significant effect for gender on the ability to recognize facial emotions. The results suggest the presence of deficits in the perception of nonverbal emotion in alexithymia.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.308

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 head0.018
GPT teacher head0.288
Teacher spread0.270 · 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