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Genetics of Opioid Dependence: A Review of the Genetic Contribution to Opioid Dependence

2014· review· en· W2147731450 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Psychiatry Reviews · 2014
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsNOSM UniversityPopulation Health Research InstituteMcMaster University
FundersCanadian Institutes of Health Research
KeywordsNarrative reviewOpioidAddictionOpioid use disorderOpioid addictionTwin studyPsychologyAddictive behaviorHeritabilityMedicinePsychiatryPsychotherapistBiologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

This narrative review aims to provide an overview of the impact of opioid dependence and the contribution of genetics to opioid dependence. Epidemiological data demonstrate that opioid dependence is a global trend with far-reaching effects on the social, economic, and health care systems. A review of classical genetic studies of opioid use suggests significant heritability of drug use behavior, however the evidence from molecular genetic studies is inconclusive. Nonetheless, certain genetic variants are important to consider given their role in the pathophysiology of addictive behavior. We undertook a literature review to identify the current state of knowledge regarding the role of genes in opioid dependence. Determining the association of genetic markers could change the current understanding of the various factors contributing to opioid dependence and therefore may improve recognition of individuals at risk for the disorder and prevention and treatment strategies.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.382
Teacher spread0.338 · 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