Influence of crank rate on the slow component of pulmonary O<sub>2</sub> uptake during heavy arm-crank exercise
Bibliographic record
Abstract
The principal aim of this study was to examine the influence of variations in crank rate on the slow component of the pulmonary oxygen uptake ((.)VO(2)) response to heavy-intensity arm-crank ergometry (ACE). We hypothesized that, for the same external work rate, a higher crank rate would elicit a greater amplitude of the (.)VO(2) "slow component". Eleven healthy males (mean (+/- SD) age, 25 ((+/-6) y; body mass, 89.1 ((+/-10.7) kg; ACE (.)VO(2)(peak), 3.36 ((+/-0.47) L x min(-1)) volunteered to participate. The subjects initially completed an incremental exercise test for the determination of (.)VO(2)(peak) and peak power on an electrically braked arm ergometer. Subsequently, they completed "step" transitions from an unloaded baseline to a work rate requiring 70% of peak power: 2 at a crank rate of 50 r x min(-1) (LO) and 2 at a crank rate of 90 r x min(-1) (HI). Pulmonary gas exchange was measured on a breath-by-breath basis and (.)VO(2) kinetics were evaluated from the mean response to each condition using non-linear regression techniques. In contradiction to our hypothesis, the (.)VO(2) slow component was significantly greater at 50 r x min(-1) than at 90 r x min(-1) (LO: 0.60 +/- 0.30 vs. HI: 0.47 +/- 0.21 L x min(-1); p < 0.05). The mean value for the localized rating of perceived exertion was also higher at 50 r x min(-1) than at 90 r x min(-1) (LO: 16.7 +/- 1.4 vs. HI: 15.2 +/- 1.3; p < 0.05), but there was no significant difference in end-exercise blood lactate concentration. It is possible that differences in muscle tension development and blood flow resulted in a greater contribution of "low-efficiency" type II muscle fibres to force production at the lower crank rate in ACE, and that this was linked to the greater (.)VO(2) slow component. However, other factors such as greater isometric contraction of the muscles of the trunk and legs at the lower crank rate might also be implicated.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".