Gender and Contraction Mode on Perceived Exertion
Bibliographic record
Abstract
The purpose of this study was to examine perceived exertion responses during concentric and eccentric elbow flexor contractions between young adult men and women. Thirty healthy young adults participated in two experimental sessions. During the first session, subjects performed five concentric isokinetic maximal voluntary contractions (MVC) of elbow flexion, followed by nine, randomly-ordered sub-maximal contractions (10-90% MVC). The same procedures were repeated during the second session, with the exception that eccentric contractions were performed. Subjects rated their perceived exertion following the sub-maximal contractions with the Borg category-ratio scale. Perceived exertion was significantly (p<0.05) less than equivalent values on the CR-10 scale at intensities greater than, and equal to, 30% MVC. A three-factor interaction between 30-40% MVC indicated that perceived exertion increased more during the eccentric, than concentric, contractions in women, while the opposite pattern was evident for the men. There were no significant contraction mode or gender differences. Power function modeling revealed that perceived exertion increased in a negatively accelerating manner, except for the men performing eccentric exercise. Perceived exertion increases in a similar non-linear manner between men and women during concentric contractions, while men exhibited a statistically linear pattern during eccentric contractions.
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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 | 0.004 |
| 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".