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Record W2038877726 · doi:10.1159/000288960

Alexithymia and Pathological Gambling

2010· article· en· W2038877726 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePsychotherapy and Psychosomatics · 2010
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPathologicalPsychologyToronto Alexithymia ScaleAddictionGambling disorderClinical psychologyImpulse control disorderPsychiatryDepression (economics)Binge eatingAddictive behaviorEating disordersMedicineInternal medicine

Abstract

fetched live from OpenAlex

Alexithymia is increased in addictive disorders such as alcoholism, cocaine abuse, and binge eating. Pathological gambling is a form of addictive disorder and may be influenced by alexithymia. We examined the association of alexithymia (Toronto Alexithymia Scale) and pathological gambling (South Oaks Gambling Screen) in 1,147 young adults; 3.1% were classified as pathological gamblers. Alexithymia was found in 31.4% of pathological gamblers, compared to 11.1% of controls; both affective and cognitive aspects of alexithymia were associated with gambling problems. The relationship was independent of depression and physical illness, and was found for both sexes, but only for Caucasians. Alexithymia may be a risk factor for pathological gambling in some populations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

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)0.0010.000

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 head0.082
GPT teacher head0.400
Teacher spread0.318 · 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