Effects of Endurance Cycling on Mechanomyographic Median Power Frequency of the Vastus Lateralis
Bibliographic record
Abstract
This study examined the effects of cycling training on mechanomyographic median power frequency (MMGMDF)–torque relationships of the vastus lateralis (VL). Ten males (Age ± SD; 20.20 ± 1.87 years) and 14 females (21.93 ± 5.33 years) performed isometric trapezoidal muscle actions with the knee extensors at 40% maximal voluntary contraction (MVC) before (PRE) and following 10 weeks of cycling training at the same absolute submaximal torque as pre-training (POSTABS). MMGMDF–torque relationships (increasing and decreasing segment) were log-transformed and b terms (slopes) were calculated. MMGMDF was averaged during steady torque. For POSTABS, the b terms for the females (0.133 ± 0.190) were greater than for the males (−0.083 ± 0.200; p = 0.013) and compared to PRE (0.008 ± 0.161; p = 0.036). At PRE, the b terms for the linearly increasing-muscle action (0.123 ± 0.192) were greater compared to the linearly decreasing-muscle action (−0.061 ± 0.188; p < 0.001), whereas no differences existed between muscle actions for POSTABS (p > 0.05). In conclusion, 10 weeks of cycling training resulted in different motor unit (MU) control strategies between sexes and altered MU control strategies between muscle actions for the VL during a moderate-intensity contraction.
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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".