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Record W2593262741 · doi:10.1017/cem.2017.1

Choosing Wisely Canada<sup>®</sup>: Five tests, procedures and treatments to question in Emergency Medicine

2017· article· en· W2593262741 on OpenAlexafffundabout
Amy Cheng, Sam Campbell, Lucas B. Chartier, Tom Goddard, Kirk Magee, Jill McEwen, Atul K. Kapur, Brian R. Holroyd, Suneel Upadhye, S. Couperthwaite, Brian H. Rowe

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsUniversity of AlbertaMcMaster UniversityAlberta Health ServicesUniversity of British ColumbiaUniversity of TorontoDalhousie UniversityUniversity Health NetworkUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of AlbertaChina Academy of Engineering PhysicsAlberta Innovates - Health SolutionsGovernment of CanadaAlberta InnovatesCanadian Association of Emergency PhysiciansAlberta Health Services
KeywordsMedicineEmergency departmentFamily medicinePediatric emergency medicineEmergency physicianNursing

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)0.008
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.776

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.004
Scholarly communication0.0070.004
Open science0.0020.003
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0500.010

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 head0.491
GPT teacher head0.550
Teacher spread0.059 · 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.

Study designNot applicable
DomainEvaluation
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

Citations30
Published2017
Admission routes3
Has abstractno

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