Announcement-Call for Papers: Why Her Heart Matters: Evidence-Based Practice and Practice-Based Evidence
Bibliographic record
Abstract
Review 1. What's new in SCAD? 2. Meeting the gap with Women Heart Health centers/clinics -The associations of sex and gender and women's heart health 3. New postpartum CVD prevention guideline 4. Patient engagement in women's CVD health 5. KT of evidence into practice through the Can Women's Heart Health Alliance and the Can Women's Heart Health Centre 6. Incorporating women's heart health into medicine/nursing curriculum 7. Unique aspects of Women's Cardiovascular Valvular Health 8. Female specific aspects of Women's Aortic Heart Health 9. Women with lived experience (WLE) in every aspect of women's heart health care 10.The Development of Chest Pain ER Protocols for Women 11.The timing hypothesis: HRT, menopause and CVD care for women 12. Prevalence and Comorbidities of PCOS in Alberta 13.Female Sex and Gender factors associated with outcomes of Cardiovascular Health 14. Issues related to access, delivery, and costs of cardiovascular care of women Systematic Review/Meta-Analysis 15.MINOCA/INOCA pathophysiology of heart disease in women Original Article 16.Women-focused cardiac rehabilitation delivery around the world and program needs to support broader implementation
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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 | 0.033 | 0.139 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.168 | 0.063 |
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".