Is the <i>V</i>O<sub>2</sub> slow component in heavy arm-cranking exercise associated with recruitment of type II muscle fibers as assessed by an increase in surface EMG?
Bibliographic record
Abstract
The recruitment of additional type II muscle fibers is one mechanism often suggested to be responsible for the slow component of oxygen uptake (VO2 (SC)). We hypothesized that surface electromyogram (EMG) of the biceps brachii, triceps brachii, anterior deltoid, and infraspinatus muscles could be related to the VO2 (SC) amplitude during arm-cranking exercises above ventilatory threshold (VT). Eight healthy subjects performed transitions from rest to 6-min heavy exercise at a constant power output of approximately 40% between VT and peak VO2. A 2-component exponential model was used to fit the VO2 response. EMG were recorded the last 15 s of each minute to obtain root mean square (RMS) and mean power frequency (MPF). Mean EMG responses for RMS and MPF were calculated by averaging EMG responses of the 4 muscles. The VO2 (SC) amplitude was of 530 +/- 166 mL/min and occurred after 134 +/- 31 s of exercise onset. Significant correlations were found for most of the subjects between EMG parameters and the VO2 SC amplitude as determined between the 2nd and the 6th minute. For all muscles, RMS values significantly increased over time during the VO2 (SC), whereas MPF decreased significantly. These results suggest a relation between the recruitment of additional type II muscle fibers and the VO2 (SC) in arm-cranking exercises.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".