Relative Contribution of Arms and Legs in 30 s Fully Tethered Front Crawl Swimming
Bibliographic record
Abstract
The relative contribution of arm stroke and leg kicking to maximal fully tethered front crawl swimming performance remains to be solved. Twenty-three national level young swimmers (12 male and 11 female) randomly performed 3 bouts of 30 s fully tethered swimming (using the whole body, only the arm stroke, and only the leg kicking). A load-cell system permitted the continuous measurement of the exerted forces, and swimming velocity was calculated from the time taken to complete a 50 m front crawl swim. As expected, with no restrictions swimmers were able to exert higher forces than that using only their arm stroke or leg kicking. Estimated relative contributions of arm stroke and leg kicking were 70.3% versus 29.7% for males and 66.6% versus 33.4% for females, with 15.6% and 13.1% force deficits, respectively. To obtain higher velocities, male swimmers are highly dependent on the maximum forces they can exert with the arm stroke (r = 0.77, P < 0.01), whereas female swimmers swimming velocity is more related to whole-body mean forces (r = 0.81, P < 0.01). The obtained results point that leg kicking plays an important role over short duration high intensity bouts and that the used methodology may be useful to identify strength and/or coordination flaws.
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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 | 0.001 | 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) | 0.001 | 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".