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Performance of the Canadian Triage and Acuity Scale for Children: A Multicenter Database Study

2012· article· en· W2001679063 on OpenAlexaffabout
Jocelyn Gravel, Eleanor Fitzpatrick, Serge Gouin, Kelly Millar, Sarah Curtis, Gary Joubert, Kathy Boutis, Chantal Guímont, Ran D. Goldman, Alexander Sasha Dubrovsky, Robert Porter, Darcy Beer, Quynh Doan, Martin H. Osmond

Bibliographic record

VenueAnnals of Emergency Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsChildren's Hospital of WinnipegJaneway Children's Health and Rehabilitation CentreUniversity of British ColumbiaCentre hospitalier de l'Université LavalBC Children's HospitalChildren's Hospital of Eastern OntarioChildren's Hospital of Western OntarioHospital for Sick ChildrenAlberta Children's HospitalIzaak Walton Killam Health CentreStollery Children's HospitalMontreal Children's HospitalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineTriageMulticenter studyScale (ratio)Medical emergencyDatabaseEmergency medicineInternal medicineRandomized controlled trialCartography

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)0.004
metaresearch head score (Gemma)0.018
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 score0.286
Threshold uncertainty score0.568

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.009
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.112
GPT teacher head0.393
Teacher spread0.281 · 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

Citations87
Published2012
Admission routes2
Has abstractno

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