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Record W2920974335 · doi:10.24095/hpcdp.39.3.03f

Aperçu - Services d’injection supervisée : mesure d’intervention communautaire en réponse à la crise des opioïdes à Ottawa (Canada)

2019· article· fr· W2920974335 on OpenAlexaffvenueabout
Sarah DelVillano, Margaret de Groh, Howard Morrison, T. Minh

Bibliographic record

VenuePromotion de la santé et prévention des maladies chroniques au Canada · 2019
Typearticle
Languagefr
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsCarleton UniversityPublic Health OntarioOttawa Public HealthUniversity of TorontoHealth CanadaPublic Health Agency of Canada
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’établissement de services d’injection supervisée (SIS) est devenu courant dans les collectivités à risque élevé afin de réagir à la crise des opioïdes qui sévit actuellement au Canada. Le service de La Roulotte (The Trailer), qui a ouvert ses portes en novembre 2017 à Ottawa (Canada), suit de près la consommation des clients, le traitement des surdoses et l'inversion des effets d’une surdose. Nous avons analysé les données recueillies entre novembre 2017 et août 2018 par ce service. Aux heures de pointe, la demande de services a constamment dépassé la capacité de La Roulotte. Le nombre de traitements de surdoses et d'inversions des effets d’une surdose a considérablement augmenté au cours de la période. D’après les résultats, La Roulotte a fourni un service important – quoique non optimal (en raison de contraintes d’espace) – de réduction des méfaits dans cette collectivité à risque élevé.

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)0.007
metaresearch head score (Gemma)0.021
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 score0.065
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.012
GPT teacher head0.308
Teacher spread0.296 · 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

Citations0
Published2019
Admission routes3
Has abstractyes

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