Introducing the Canadian Women’s Heart Health Alliance ATLAS on the Epidemiology, Diagnosis, and Management of Cardiovascular Diseases in Women
Bibliographic record
Abstract
Despite a global understanding that indicators and outcomes of cardiovascular disease (CVD) are known to differ between men and women, uptake of the recognition of sex and gender influences on the clinical care of women has been slow or absent. The Canadian Women's Heart Health Alliance (CWHHA) was established as a network of experts and advocates to develop and disseminate evidence-informed strategies to transform clinical practice and augment collaborative action on women's cardiovascular health in Canada. As an initial project, the CWHHA membership undertook an environmental scan of CVD in women in Canada from which a scientific statement could be developed to summarize critical sex- and gender-specific issues in CVD. This comprehensive review of the evidence focused on the sex- and gender-specific differences in comorbidity, risk factors, disease awareness, presentation, diagnosis, and treatment across the entire spectrum of CVD. In the process of creating the review, it was recognized that the team of CWHHA experts had also assembled an expansive collection of original research articles that were synthesized into detailed chapters reporting on the present state of the evidence unique to each cardiovascular condition in women. This work comprises an "ATLAS" on the epidemiology, diagnosis, and management of CVD in women. The overall goal of the ATLAS is to create a living document that will help clinicians and the public recognize the unique aspects of women's heart health care and provide policy makers with information they need to ensure equitable care for women with CVD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".