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Record W4297094171 · doi:10.1007/s12630-022-02328-8

Strategies to prevent long-term opioid use following trauma: a Canadian practice survey

2022· article· en· W4297094171 on OpenAlexafffundabout
Mélanie Berube, Caroline Côté, Lynne Moore, Alexis F. Turgeon, Étienne L. Belzile, Andréane Richard‐Denis, Craig Dale, Gregory Berry, Manon Choinière, M. Gabrielle Pagé, Line Guénette, Sébastien Dupuis, Lorraine N. Tremblay, Valérie Turcotte, Marc-Olivier Martel, Claude-Édouard Châtillon, Kadija Perreault, François Lauzier

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecHealth Sciences CentreSunnybrook Health Science CentreMcGill UniversityMcGill University Health CentreCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversity of TorontoCentre Hospitalier de l’Université de MontréalUniversité LavalUniversité de MontréalThe Quebec Population Health Research Network
FundersInstitute of Health Services and Policy ResearchFonds de Recherche du Québec - SantéRéseau québécois de recherche sur la douleur
KeywordsMedicineEconomic shortageMedical prescriptionFamily medicineNursingPopulationNonsteroidalEnvironmental health

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.270
Teacher spread0.248 · 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

Citations2
Published2022
Admission routes3
Has abstractno

Explore more

Same venueCanadian Journal of Anesthesia/Journal canadien d anesthésie→Same topicOpioid Use Disorder Treatment→French-language works237,207→