The Effects of Different Warm-up Volumes on the 100-m Swimming Performance
Bibliographic record
Abstract
The aim of this study was to compare the effect of 3 different warm-up (WU) volumes on 100-m swimming performance. Eleven male swimmers at the national level completed 3 time trials of 100-m freestyle on separate days and after a standard WU, a short WU (SWU), or a long WU (LWU) in a randomized sequence. All of them replicated some usual sets and drills, and the WU totaled 1,200 m, the SWU totaled 600 m, and the LWU totaled 1,800 m. The swimmers were faster after the WU (59.29 seconds; confidence interval [CI] 95%, 57.98-60.61) and after the SWU (59.38 seconds; CI 95%, 57.92-60.84) compared with the LWU (60.18 seconds; CI 95%, 58.53-61.83). The second 50-m lap after the WU was performed with a higher stroke length (effect size [ES] = 0.77), stroke index (ES = 1.26), and propelling efficiency (ES = 0.78) than that after the SWU. Both WU and SWU resulted in higher pretrial values of blood lactate concentrations [La] compared with LWU (ES = 1.58 and 0.74, respectively), and the testosterone:cortisol levels were increased in WU compared with LWU (ES = 0.86). In addition, the trial after WU caused higher [La] (ES ≥ 0.68) and testosterone:cortisol values compared with the LWU (ES = 0.93). These results suggest that an LWU could impair 100-m freestyle performance. The swimmers showed higher efficiency during the race after a 1200-m WU, suggesting a favorable situation. It highlighted the importance of the [La] and hormonal responses to each particular WU, possibly influencing performance and biomechanical responses during a 100-m race.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".