Changes in exercise hyperpnea are more attributable to limb movement frequency than pedal loading
Bibliographic record
Abstract
The significance of limb movement frequency in determining ventilation during exercise remains a contested topic in respiratory research. We used two sinusoidal exercise protocols on a cycle ergometer to separately assess the effects of limb movement frequency i.e. cadence (CP) and pedal load (LP) on ventilation. During the first test, cadence was altered sinusoidally while pedal load remained constant. In the second test, pedal load changed sinusoidally while cadence was constant. Variables were fitted to a sinusoid with parameters amplitude, mean, period, and phase angle lag. Five participants completed both protocols. Mean (SD) cadence amplitudes differed between protocols (CP: 23.5 (0.67) rpm, LP: 0.47 (0.3) rpm, p<0.001). The phase lag angles for ventilation also differed, with sinusoidal cadence significantly smaller than sinusoidal load (CP: 23.7 (12.7) deg., LP: 48.1 (14.6) deg., p= 0.023). However the mean ventilation was not different between tests (CP: 44.5 (3.9) L/min, LP: 46.8 (4.2) L/min, p=0.99). VO 2 and VCO 2 did not differ between tests; eliminating the possibility that changes in ventilatory response between protocols resulted from differences in metabolism. Therefore we concluded that changes in exercise hyperpnea are more attributable to limb movement frequency than pedal loading. Funding provided by the Faculty of Kinesiology and Physical Education at the University of Toronto
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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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".