The independent effects of age and sex in performance fatigability profile after a ramp incremental cycling test
Bibliographic record
Abstract
PURPOSE: To investigate the effects of age and sex in performance fatigability profile after a ramp incremental (RI) test. METHODS: max) and peak power output (POpeak) were measured. RESULTS: max and POpeak compared to older counterparts (all p < 0.05). The IMVC declined more in young (females: -27 ± 14%; males: -44 ± 7%) than older (females: -23 ± 9%; males: -26 ± 9%) (p < 0.01), and in males compared to females (p < 0.01). Single twitch declined more in young (females: -43 ± 15%; males: -54 ± 15%) than older participants (females: -33 ± 10%; males: -27 ± 18%) (p = 0.01), without sex differences (p = 0.59). Similar responses were observed for 100 Hz and 10 Hz stimulus for age and sex (all p > 0.05). Voluntary activation was not different (p = 0.11) between young (females: -5 ± 5%; males: -8 ± 6%) and older (females: -7 ± 6%; males: -12 ± 6%), but declined less in females than males (p = 0.03). There was no age × sex interaction for any performance fatigability outcome (all p ≥ 0.06). CONCLUSION: Contractile function was more impaired in young than older participants, whereas males showed greater decline in VA than females. There was no combined effect of age and sex in performance fatigability responses.
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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 | 0.001 | 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".