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Record W2277762392 · doi:10.1016/j.cjca.2016.02.059

The Development and Feasibility Assessment of Canadian Quality Indicators for Atrial Fibrillation

2016· article· en· W2277762392 on OpenAlexaffvenueabout
Jafna L. Cox, Sulan Dai, Yanyan Gong, Robert S. McKelvie, M. Sean McMurtry, Garth H. Oakes, Allan C. Skanes, Atul Verma, Stephen B. Wilton, D. George Wyse

Bibliographic record

VenueCanadian Journal of Cardiology · 2016
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of CalgaryLibin Cardiovascular Institute of AlbertaSouthlake Regional Health CenterWestern UniversityMcMaster UniversityUniversity of AlbertaPopulation Health Research InstituteOntario Stroke NetworkCanadian Institute for Health InformationPublic Health Agency of CanadaDalhousie University
Fundersnot available
KeywordsMedicineAtrial fibrillationCanadian Cardiovascular SocietyStroke (engine)Quality managementQuality assuranceQuality (philosophy)Atrial flutterMEDLINEIntensive care medicineMedical emergencyOperations managementInternal medicineAngina

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)0.109
metaresearch head score (Gemma)0.185
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.185
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.008
Science and technology studies0.0040.001
Scholarly communication0.0050.002
Open science0.0030.004
Research integrity0.0010.003
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 head0.111
GPT teacher head0.381
Teacher spread0.269 · 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 designNot applicable
Domainnot available
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

Citations12
Published2016
Admission routes3
Has abstractno

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