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Record W2024957938 · doi:10.1503/cmaj.101508

Harmonization of guidelines for the prevention and treatment of cardiovascular disease: the C-CHANGE Initiative

2011· article· en· W2024957938 on OpenAlexafffundvenue
Sheldon W. Tobe, James A. Stone, Melissa Brouwers, Onil Bhattacharyya, Kimberly M. Walker, Martin Dawes, Jacques Genest, Steven A. Grover, Gordon Gubitz, David C.W. Lau, Andrew Pipe, Peter Selby, Mark S. Tremblay, Darren E. R. Warburton, Richard Ward, Vincent Woo, Lawrence A. Leiter, Peter P. Liu

Bibliographic record

VenueCanadian Medical Association Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineHarmonizationDiseaseIntensive care medicineDisease managementChronic diseaseInternal medicine

Abstract

fetched live from OpenAlex

Cardiovascular disease is the most prevalent chronic medical condition in Canada, and evidence-based management of risk factors for cardiovascular disease can reduce morbidity and mortality.[1][1] However, there are more than 400 individual recommendations for risk management of cardiovascular

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.265
metaresearch head score (Gemma)0.431
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.906

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2650.431
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0120.014
Science and technology studies0.0050.004
Scholarly communication0.0100.005
Open science0.0130.011
Research integrity0.0140.020
Insufficient payload (model declined to judge)0.0040.002

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 head0.413
GPT teacher head0.445
Teacher spread0.032 · 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 designNot applicable
DomainMethods
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

Citations69
Published2011
Admission routes3
Has abstractyes

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