Relationship between laboratory-measured variables and heart rate during an ultra-endurance triathlon
Bibliographic record
Abstract
The aim of the present study was to examine the relationship between the performance heart rate during an ultra-endurance triathlon and the heart rate corresponding to several demarcation points measured during laboratory-based progressive cycle ergometry and treadmill running. Less than one month before an ultra-endurance triathlon, 21 well-trained ultra-endurance triathletes (mean +/- s: age 35 +/- 6 years, height 1.77 +/- 0.05 m, mass 74.0 +/- 6.9 kg, = 4.75 +/- 0.42 l x min(-1)) performed progressive exercise tests of cycle ergometry and treadmill running for the determination of peak oxygen uptake (VO2peak), heart rate corresponding to the first and second ventilatory thresholds, as well as the heart rate deflection point. Portable telemetry units recorded heart rate at 60 s increments throughout the ultra-endurance triathlon. Heart rate during the cycle and run phases of the ultra-endurance triathlon (148 +/- 9 and 143 +/- 13 beats x min(-1) respectively) were significantly (P < 0.05) less than the second ventilatory thresholds (160 +/- 13 and 165 +/- 14 beats x min(-1) respectively) and heart rate deflection points (170 +/- 13 and 179 +/- 9 beats x min(-1) respectively). However, mean heart rate during the cycle and run phases of the ultra-endurance triathlon were significantly related to (r = 0.76 and 0.66; P < 0.01), and not significantly different from, the first ventilatory thresholds (146 +/- 12 and 148 +/- 15 beats x min(-1) respectively). Furthermore, the difference between heart rate during the cycle phase of the ultra-endurance triathlon and heart rate at the first ventilatory threshold was related to marathon run time (r = 0.61; P < 0.01) and overall ultra-endurance triathlon time (r = 0.45; P < 0.05). The results suggest that triathletes perform the cycle and run phases of the ultra-endurance triathlon at an exercise intensity near their first ventilatory threshold.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".