Electromyographic, mechanomyographic, and metabolic responses during cycle ergometry at a constant rating of perceived exertion
Bibliographic record
Abstract
Ten subjects performed four 8-min rides (65%-80% peak oxygen consumption) to determine the physical working capacity at the OMNI rating of perceived exertion (RPE) threshold (PWCOMNI). Polynomial regression analyses were used to examine the patterns of responses for surface electromyographic (EMG) amplitude (EMG AMP), EMG mean power frequency (EMG MPF), mechanomyographic (MMG) AMP, and MMG MPF of the vastus lateralis as well as oxygen consumption rate, respiratory exchange ratio (RER), and power output (PO) were examined during a 1-h ride on a cycle ergometer at a constant RPE that corresponded to the PWCOMNI. EMG AMP and MMG MPF tracked the decreases in oxygen consumption rate, RER, and PO, while EMG MPF and MMG AMP tracked RPE. The decreases in EMG AMP and MMG MPF were likely attributable to decreases in motor unit (MU) recruitment and firing rate, while the lack of change in MMG AMP may have resulted from a balance between MU de-recruitment as PO decreased, and an increase in the ability of activated fibers to oscillate. The current findings suggested that during submaximal cycle ergometry at a constant RPE, MU de-recruitment and mechanical changes within the muscle may influence the perception of effort via feedback from group III and IV afferents.
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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) | 0.000 | 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) | 0.001 | 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".