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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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations39
Published2023
Admission routes4
Has abstractno

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