The effect of age and gender on the relative fatigability of the human adductor pollicis muscle
Bibliographic record
Abstract
The purpose of this study was to examine the relative influence of such factors as age, gender, and absolute force on the fatiguability of the human adductor pollicis muscle. 12 young males (YM, 25.3 +/- 2.1 y), 12 young females (YF. 23.5 +/- 2.1 y), 12 older males (OM, 71.7 +/- 5.6 y) and 12 older females (OF, 69.5 +/- 4.6 y) participated. Three minutes of intermittent (5 s contraction, 2 s rest) maximal voluntary contractions (MVC) were used to fatigue the adductor pollicis muscle; the ulnar nerve was also stimulated in each 2 s rest period to evoke a maximal twitch. Males were stronger than females in both voluntary and evoked force (PT) in the young age group (MVC: YM, 10.0 +/- 2.7 kg vs. YF, 6.6 +/- 1.1 kg, P < 0.05) (PT: YM, 0.99 +/- 0.21 kg vs. YF, 0.71 +/- 0.12 kg, P < 0.05). In the older adults, however, males were stronger only in the evoked twitch (OM, 0.73 +/- 0.24 kg vs. OF, 0.48 +/- 0.07 kg, P < 0.05). There was no significant effect of gender or absolute muscle force on relative fatigability; the only variable found to significantly affect fatigability was age. Older adults were significantly less fatigable than young adults as indicated by the voluntary fatigue index (FI) (percentage of force reduction from baseline; FI-young, 40.2 +/- 12.6% vs. FI-old, 25.2 +/- 12.3%). This age effect, however, was more prominent in males than females (FI-YM, 44.7 +/- 10.5% vs. FI-OM, 24.2 +/- 10.7%, P < 0.01; FI-YF, 37.8 +/- 14.1% vs. FI-OF, 26.3 +/- 14.5%, P = 0.13). In conclusion, age was found to be the strongest single predictor of fatigability during short duration, intermittent exercise in human adductor pollicis muscle.
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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".