The effects of sex and contraction intensity on fatigability and muscle oxygenation in trained individuals
Bibliographic record
Abstract
Fatigability varies depending on sex and contraction intensity during sustained exercise. This study examined the responses of time to task failure (TTF), performance fatigability (PF), and muscle oxygenation (SmO2) in males and females during isometric handgrip holds to failure (HTF) at 30% and 60% maximum voluntary isometric contraction (MVIC). Males ( n = 12) and females ( n = 12) performed a pre-MVIC, handgrip HTF at randomly ordered percentages of MVIC (either 30% or 60%), followed by a post-MVIC on the dominant arm. During the HTF testing, the TTF and SmO2 responses were recorded, and PF was determined from the pre- to post-MVICs. TTF for 30% MVIC HTF was greater than 60% MVIC HTF ( p < 0.001), but was not different between males and females ( p = 0.117). PF exhibited an inverse relationship with intensity for each sex, while males demonstrated greater PF than females for both 30% and 60% MVIC HTF. For the 60% MVIC HTF, males demonstrated greater desaturation than females (CI95% = [−28.1, −2.6%], p = 0.021, d = 0.621), but not for the 30% MVIC HTF (CI95% = [−12.2, 7.9%], p = 0.315, d = 0.621). Sex differences in PF and SmO2 may be attributed to the differences in muscle mass, absolute strength, contractile properties, and muscle metabolism between males and females. However, these proposed differences between males and females may not fully inform exercise performance (e.g., TTF). Sex-specific fatigue responses may be affected by complex physio-psychological mechanisms, and therefore, additional investigations under diverse exercise conditions are required to better prescribe exercise for both males and females.
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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) | 0.002 | 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".