MétaCan
Menu
Back to cohort
Record W2144645566 · doi:10.1017/s1481803500005777

A consensus-based process to define standard national data elements for a canadian emergency department information system

2001· article· en· W2144645566 on OpenAlexaffabout
Grant Innes, Michael J. Murray, Eric Grafstein

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2001
Typearticle
Languageen
FieldHealth Professions
TopicMedical Coding and Health Information
Canadian institutionsRoyal Victoria Regional Health CentreSt. Paul's HospitalCanadian Institute for Health Information
Fundersnot available
KeywordsEmergency departmentContext (archaeology)Minimum Data SetMedicineMedical emergencyHealth careNursingPolitical scienceGeography

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)0.357
metaresearch head score (Gemma)0.397
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.923
Threshold uncertainty score0.793

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3570.397
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0230.015
Science and technology studies0.0220.007
Scholarly communication0.0190.010
Open science0.0140.014
Research integrity0.0070.015
Insufficient payload (model declined to judge)0.0060.003

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 head0.416
GPT teacher head0.507
Teacher spread0.091 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainReporting
GenreMethods

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

Citations39
Published2001
Admission routes2
Has abstractno

Explore more

Same venueCanadian Journal of Emergency MedicineSame topicMedical Coding and Health InformationFrench-language works237,207