MACE in the Race: A Canadian Perspective on Major Adverse Cardiac Events (MACE) During Running
Bibliographic record
Abstract
The recent tragic deaths of two fit and healthy Canadian physicians during running have shocked the whole Canadian medical community. In order to prevent such loss of precious human lives, the paradox of dying during a life-prolonging activity begets further contemplation and investigation on whether we have been missing something in assessing the risk of major cardiovascular adverse events (MACE) in fit individuals during long-distance running. Additionally, knowing the potential, yet the rare fatal risk of running, physicians are obliged to disclose that fatal risk while prescribing exercise to their patients according to the Supreme Court of Canada Ruling. Further research is urgently needed.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.033 | 0.040 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".