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Record W3033175269 · doi:10.1016/j.ssmph.2020.100609

Opioid agonist therapy trajectories among street entrenched youth in the context of a public health crisis

2020· article· en· W3033175269 on OpenAlexafffundabout
Valerie Giang, Madison Thulien, Ryan McNeil, Kali Sedgemore, Haleigh Anderson, Danya Fast

Bibliographic record

VenueSSM - Population Health · 2020
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of British ColumbiaBritish Columbia Centre on Substance Use
FundersCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute on Drug AbuseVancouver Foundation
KeywordsPolysubstance dependenceContext (archaeology)BuprenorphineMental healthMedicinePsychiatryPublic healthMethadoneOpioid use disorderPsychologySubstance abuseOpioidNursing

Abstract

fetched live from OpenAlex

North America is in the midst of an overdose crisis that is having devastating effects among street entrenched youth (<30 years of age). Opioid agonist therapy (OAT) is a cornerstone of the public health response to this crisis; yet, we struggle to connect youth to OAT across numerous settings. This qualitative study examined perspectives on OAT among street entrenched youth and their providers in Vancouver, Canada. Our findings reveal youth's hopes and fears surrounding making a "full" recovery from past substance use. Youth often equated getting off opioids with "getting back to normal" and the ability to pursue "normal" kinds of futures. While many initiated OAT for short periods of time (

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.228
Threshold uncertainty score0.454

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.338
Teacher spread0.249 · 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 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

Citations41
Published2020
Admission routes3
Has abstractyes

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