The Relationship of the Heart Rate Deflection Point to the Ventilatory Threshold in Trained Cyclists
Bibliographic record
Abstract
The purpose of this study was to assess the relationship of the heart rate deflection point (HRDP) to the ventilatory threshold (VT) in trained cyclists. Twenty-one endurance-trained cyclists (mean +/- SD: Vo(2)max = 67.6 +/- 4.7 ml x kg x min(-1)) completed a maximal cycle ergometer test of volitional fatigue using a ramped protocol. Ventilatory variables (Ve, Vo(2), Vco(2)) and power were measured online with averages reported every 20 seconds. Heart rate (HR) was recorded every 20 seconds using a Polar monitor. VT was calculated using the excess CO(2) elimination curve. The first derivative of a logistic growth curve fit to the HR-power data produced the HRDP. No significant differences (p > 0.01) existed between HR values at HRDP (171.7 +/- 9.6 b x min(-1)) and VT (169.8 +/- 9.9 b x min(-1)) or between Vo(2) values at HRDP (53.6 +/- 4.2 ml x kg x min(-1)) and VT (52.2 +/- 4.8 ml x kg x min(-1)). But power values at HRDP (318.7 +/- 30.7 W) were significantly different (p < 0.01) from those at VT (334.8 +/- 36.7 W). There were significant relationships between HRDP and VT for the physiological variables of HR (r = 0.92, p < 0.001), Vo(2) (r = 0.72, p < 0.001), and power (r = 0.77, p < 0.001). These findings indicate that HR and Vo(2) at HRDP are not significantly different from the values at VT in trained cyclists. HR values derived from HRDP may be used to set parameters for training intensity. Variability in the speed/power-HRDP relationship across detrained/trained states may be used to evaluate training programs.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".