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Record W2615076155 · doi:10.1177/0706743717711167

The State of Opioid Agonist Therapy in Canada 20 Years after Federal Oversight

2017· review· en· W2615076155 on OpenAlexaffvenueabout
Joseph K. Eibl, Kristen A. Morin, Esa Leìnonen, David C. Marsh

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2017
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsLaurentian UniversityNOSM University
Fundersnot available
KeywordsMethadoneBuprenorphineContingency managementMedicineHeroinBusinessAddictionOpioidNursingPsychiatryIntervention (counseling)Drug

Abstract

fetched live from OpenAlex

Opioid agonist therapy was introduced in Canada in 1959 with the use of methadone for the treatment of opioid dependence. The regulation of methadone was the responsibility of Health Canada until 1995, when oversight was transferred to the provincial health systems. During the more than 20 years since the federal health authority transferred oversight of methadone to the provincial level, methadone programming has evolved differently in every province. The landscape of opioid dependence treatment is varied across the country, with generally increasing treatment capacity in all provinces and dramatic increases in some. Each province has an independent methadone program with differing policies, contingency management strategies, laboratory monitoring policies, and delivery methods. Treatment options have increased, with buprenorphine- and heroin-assisted treatment becoming available to limited degrees. Despite this, access remains a challenge in many parts of the country (particularly rural and remote areas) because the demand for treatment has increased even more rapidly than the capacity. Although treatment access remains a priority in many jurisdictions, there is also a need to attend to treatment quality as treatment access expands, including integration with addiction counselling, primary care, and mental health care. As well, coordinated monitoring and reporting of treatment need, quality, and delivery are required; implementing a national policy to promote planning would have tremendous value.

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 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 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 score0.946
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.292
Teacher spread0.269 · 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 teacher head, 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

Citations100
Published2017
Admission routes3
Has abstractyes

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