Sex-related differences in motor unit firing rate and pennation angle
Bibliographic record
Abstract
Motor unit firing rate (MUFR) and pennation angle were measured concurrently in males and females from submaximal to maximal intensities. Thirty participants, (16 female, 14 male) performed isometric dorsiflexion contractions at 20%, 40%, 60%, 80%, and 100% of maximal voluntary contraction (MVC). During each contraction, measures of MUFR were obtained via surface electromyography decomposition, and muscle fiber pennation angle and fascicle length were obtained via ultrasound. There was no significant interaction effect of sex and contraction intensity present for mean MUFR ( p = 0.24), pennation angle ( p = 0.98), or fascicle length ( p = 0.81). Males had greater mean MUFR ( p < 0.001), pennation angle ( p = 0.02), and fascicle length ( p = 0.03) compared to females. In general, mean MUFR ( p < 0.001) and pennation angle ( p < 0.02) increased with increasing contraction intensity; however, fascicle length ( p = 0.30) was similar across contraction intensities. There were no significant relationships between mean MUFR and pennation angle for males ( r = 0.18, p = 0.13) or females ( r = 0.20, p = 0.09), nor between mean MUFR and fascicle length for males ( r = 0.20, p = 0.10) or females ( r = 0.21, p = 0.07). Although sex-related differences in MUFR, pennation angle, and fascicle length were present, there were no relationships between MUFR and the muscle properties. These results suggest that sex-related differences in mean MUFR may not be associated with the sex-related differences in the muscle architectural properties currently investigated.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".