MétaCan
Menu
Back to cohort
Record W4388005647 · doi:10.1016/j.cjca.2023.09.020

The Canadian Cardiovascular Society Classification of Acute Atherothrombotic Myocardial Infarction Based on Stages of Tissue Injury Severity: An Expert Consensus Statement

2023· article· en· W4388005647 on OpenAlexafffundvenueabout
Andreas Kumar, Kim A. Connelly, Keyur Vora, Kevin R. Bainey, Andrew G. Howarth, Jonathon Leipsic, Frank S. Prato, Howard Leong‐Poi, Anthony Main, Rony Atoui, Jacqueline Saw, Éric Larose, Michelle M. Graham, Marc Ruel, Rohan Dharmakumar

Bibliographic record

VenueCanadian Journal of Cardiology · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsUniversity of OttawaUniversité LavalLawson Health Research InstituteLibin Cardiovascular Institute of AlbertaVancouver General HospitalUniversity of CalgaryHealth Sciences NorthWestern UniversityUniversity of TorontoCanadian VIGOUR CentreUniversity of AlbertaSt. Michael's HospitalUniversity of British ColumbiaNOSM University
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthUniversity of TorontoNorthern Ontario Academic Medicine Association
KeywordsMedicineStatement (logic)Myocardial infarctionConsensus conferenceCardiologyInternal medicineIntensive care medicineLaw

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)0.026
metaresearch head score (Gemma)0.034
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.034
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.010
Bibliometrics0.0100.007
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0120.004
Research integrity0.0050.013
Insufficient payload (model declined to judge)0.0030.003

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 head0.046
GPT teacher head0.335
Teacher spread0.289 · 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

Citations39
Published2023
Admission routes4
Has abstractno

Explore more

Same venueCanadian Journal of CardiologySame topicAcute Myocardial Infarction ResearchFrench-language works237,207