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Record W2144728439 · doi:10.1017/s1092852900015121

The Genetics of Gambling and Behavioral Addictions

2006· review· en· W2144728439 on OpenAlexaff
Daniela S. S. Lobo, James L. Kennedy

Bibliographic record

VenueCNS Spectrums · 2006
Typereview
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsAddictionBehavioural geneticsBehavioral addictionPsychologyPathologicalPsychiatryMedicineDevelopmental psychologyPathology

Abstract

fetched live from OpenAlex

Behavioral addictions are considered as the repetitive occurrence of impulsive behaviors without consideration of their potential negative consequences. These addictions represent an increasing cost to society and are an important new field of research in psychiatric genetics. There has been a growing body of evidence on the familial aggregation and genetic influences on the development of behavioral addictions and mainly on pathological gambling. The aim of this article is to critically review findings of family and molecular genetic studies on behavioral addictions, focusing on pathological gambling and commenting on other disorders where appropriate. This review provides a comprehensive approach to genetic studies on behavioral addiction and points out the necessity of expanding the genetic research in this field. Future directions for genetic studies in this field are also discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.262
GPT teacher head0.486
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations71
Published2006
Admission routes1
Has abstractyes

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