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Record W2171430252 · doi:10.1177/009145090903600114

Relapse to Injecting Drug Use: A Hepatitis C Treatment Concern

2009· article· en· W2171430252 on OpenAlexaboutno aff
Magdalena Harris

Bibliographic record

VenueContemporary Drug Problems · 2009
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHepatitis CHepatitisQuarter (Canadian coin)DrugFamily medicineHepatitis BInjection drug usePerspective (graphical)Intensive care medicinePsychiatryInternal medicineDrug injection

Abstract

fetched live from OpenAlex

In light of current initiatives to increase hepatitis C treatment uptake amongst current and former injectors, this article aims to explore the barriers and facilitators to treatment uptake from the patient's perspective. Semistructured interviews were conducted with people living with hepatitis C in Auckland, New Zealand and Sydney, Australia in 2004 and 2006. This article explores in detail one significant issue that has not so far been addressed in the social research literature about decision making for hepatitis C treatment. This is the concern expressed by a quarter of the 34 ex-injecting participants regarding the potential for hepatitis C treatment to cause a relapse to injecting drug use. The connection between hepatitis C treatment and relapse to injecting drug use is supported by a substantial clinical literature. Thus the proposed expansion of hepatitis C treatment into alcohol and other drug settings needs to be undertaken with caution.

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)0.004
metaresearch head score (Gemma)0.013
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 score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.003
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 head0.092
GPT teacher head0.337
Teacher spread0.245 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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