The influence of race length on arterial compliance following an ultra‐endurance marathon
Bibliographic record
Abstract
There is inconclusive evidence concerning the effects of routine participation in ultra-endurance events on cardiovascular disease (CVD) risk. Arterial compliance is a reliable, non-invasive, and effective tool for evaluating CVD risk. The purpose of this research was to examine if race length influences acute changes in arterial compliance following an ultra-marathon event. A total of 46 ultra-marathon runners were recruited including 21 participants (39.8 ± 8.3 years, 6 females) in the 80-km event and 25 participants (43.7 ± 9.8 years, 3 female) in the 195-km event. Arterial compliance was measured via radial applanation tonometry (CR-2000, HDI) for diastolic pulse contour analysis before and following the race. Significant between-group differences were found for changes in large arterial compliance with a decrease (increase in stiffness) following the 195-km event and an increase following the 80-kilometre event (p < .05). Longer race lengths are associated with greater reductions in large arterial compliance following recreational ultra-marathon running. Assessment of arterial compliance might be a useful prognostic tool to assess the long-term risk of CVD among ultra-marathon runners.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".