The Duality of Screening Mammography: Advancing Women’s Cardiovascular Health
Bibliographic record
Abstract
In recent years, there have been substantial efforts by the medical community to reduce the cardiovascular disease (CVD) burden in women, as it remains a leading cause of mortality and morbidity in women worldwide.1 In developed nations such as the United States and Canada, the decline in cardiovascular mortality for women has stagnated since 2017, with mortality rates now increasing.2 Reasons for this trend are not clear, but may be related to disparities in identification, diagnosis, treatment, and underrepresentation of women in clinical trials.
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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 | 0.014 | 0.054 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.044 | 0.041 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".