Effect of Low Recumbent Angle on Cycling Performance, Fatigue, and V˙O2 Kinetics
Bibliographic record
Abstract
PURPOSE: This study aimed to examine the effect of the degree of inclination from upright to supine postures on cycling performance, fatigue, and oxygen uptake (V˙O(2)) kinetics. METHODS: In experiment 1, 10 subjects performed graded and fatigue (exhaustive constant-load heavy exercise with 10 s all-out efforts interspersed every minute) tests at four cycling postures: upright, 30° recumbent (R), 15° R, and supine. In experiment 2, nine different subjects performed two bouts of constant-load heavy exercise in the same four cycling postures. Bout 1 was brought to failure, and bout 2 was limited to 6 min, so that the breath-by-breath V˙O(2) data from the first 6 min of each bout were averaged and curve fit. RESULTS: The time sustained during the graded test was significantly shorter in the supine compared with the other three postures and also shorter in the 15° R compared with the upright. The rate of fatigue was higher in the supine compared with the other three postures, and the normalized EMG activities of three leg muscles at end exercise were larger in the supine (and in some cases 15° R) compared with upright posture. The time sustained (min) during high-intensity constant-load cycling was significantly longer during upright (12.8 ± 5.3) and 30° R (14.2 ± 6.1) compared with 15° R (8.5 ± 1.7) and supine (6.8 ± 2.0) postures, but the amplitudes of the slow component of the V˙O(2) response (L·min) were larger during 15° R (0.57 ± 0.10) and supine (0.61 ± 0.15) compared with 30° R (0.39 ± 0.12) and also larger in the supine than upright (0.43 ± 0.13) postures. Inert gas rebreathing analysis revealed similar cardiac output responses at 60 s into the exercise among postures. CONCLUSION: Lowering the recumbent angle to 15° resulted in shorter performance, larger fatigue, and altered V˙O(2) kinetics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".