Sex differences in the modulation of the motor unit discharge rate leads to reduced force steadiness
Bibliographic record
Abstract
The purpose of this study was to evaluate the relationship between the variability in the motor unit inter-pulse interval and force steadiness at submaximal and maximal force outputs between the sexes. Twenty-four male and 24 female participants were recruited to perform isometric dorsiflexion contractions at 20, 40, 60, 80, and 100% maximum voluntary contraction. Tibialis anterior myoelectric signal was recorded by an intramuscular electrode. Females had lower force steadiness (coefficient of variation of force (CoV-Force), 27.3%, p < 0.01) and a greater coefficient of variation of motor unit action potential inter-pulse interval (CoV-IPI), compared with males (9.6%, p < 0.01). There was no significant correlation between the normalized CoV-IPI and CoV-Force (r = 0.19, p > 0.01), but there was a significant repeated measures correlation between the raw scores for root-mean-square force error and the standard deviation of motor unit discharge rate (r = 0.65, p < 0.01). Females also had a greater incidence of doublet discharges on average across force levels (p < 0.01). The sex differences may result from motor unit behaviours (i.e., doublet and rapid discharges, synchronization, rate coding or recruitment), leading to lower force steadiness and greater CoV-IPI in females. Novelty: Sex differences in force steadiness may be due to neural strategies. Females have lower force steadiness compared with males. Greater incidence of doublet discharges in females may result in lesser force steadiness.
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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) | 0.004 | 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".