Objective and Subjective Assessments of Exercise Burden in Masters Athletes Are Poorly Correlated
Bibliographic record
Abstract
ABSTRACT Accurate quantification of exercise volume (burden) is crucial for understanding links between exercise and cardiovascular outcomes in older endurance athletes (EA). Exercise burden, an integral of intensity and duration (MET·min), is typically determined from subjective self-reports but has uncertain accuracy. We studied 40 EAs (41 to 69 yrs., 50% female) with >10 yrs. training history, during a typical outdoor cycling training session (42 km). Subjective self-reports were related to cardiac (HR·min) and metabolic (MET·min) components of exercise burden, monitored continuously. Subjective self-reports were highly variable and underestimated objective metrics of exercise intensity. Discordance was observed between metabolic and cardiac burden as less fit individuals accrued greater cardiac (14039±2649 vs. 11784±1132 HR·min , P <0.01) but lower metabolic burden (808±59 vs. 858±61 MET·min, P <0.05) vs. higher fit EA. Caution is advised in interpreting MET·min estimates from self-reports, urging objective measurement of cardiac burden for further insights into the risk-benefit relationship of long-term exercise.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".