Differences in ratings of perceived exertion between the sexes during single-joint and whole-body exercise
Bibliographic record
Abstract
The objective of the present study was to examine ratings of perceived exertion (RPE) between adult men (n = 10) and women (n = 10) during two different modes of fatiguing exercise. Participants provided their rating of perceived exertion (6-20 scale) while performing single-leg heel raises and exercise on a rowing ergometer, during two separate experimental sessions. During the heel raise exercise, ratings of perceived exertion were reported for the exercising calf muscles, while a single undifferentiated and two differentiated ratings were obtained during the rowing exercise. Perceived exertion responses were standardized across the exercise duration between participants, via linear interpolation and power function modelling. No significant differences were observed between the sexes in number of heel raises; however, women exercised significantly (P < 0.05) longer during the rowing exercise. No significant differences were observed between the sexes for ratings of perceived exertion obtained via linear interpolation. However, power function modelling revealed greater (P < 0.05) increases for women during the heel raises. The findings of the present study suggest the presence of a subtle difference in the perceived exertion response between the sexes when modelled as a power function during single-joint exercise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".