Effects of Varying Post-Warm-Up Recovery Time on 200-m Time-Trial Swim Performance
Bibliographic record
Abstract
CONTEXT: Warm-up before athletic competition might enhance performance by affecting various physiological parameters. There are few quantitative data available on physiological responses to the warm-up, and the data that have been reported are inconclusive. Similarly, it has been suggested that varying the recovery period after a standardized warm-up might affect subsequent performance. PURPOSE: To determine the effects of varying post-warm-up recovery time on a subsequent 200-m swimming time trial. METHODS: Ten national-caliber swimmers (5 male, 5 female) each swam a 1500-m warm-up and performed a 200-m time trial of their specialty stroke after either 10 or 45 min of passive recovery. Subjects completed 1 time trial in each condition separated by 1 wk in a counterbalanced order. Blood lactate and heart rate were measured immediately after warm-up and 3 min before, immediately after, and 3 min after the time trial. Rating of perceived exertion was measured immediately after the warm-up and time trial. RESULTS: Time-trial performance was significantly improved after 10 min as opposed to 45 min recovery (136.80 +/- 20.38 s vs 138.69 +/- 20.32 s, P < .05). There were no significant differences between conditions for heart rate and blood lactate after the warm-up. Pre-time-trial heart rate, however, was higher in the 10-min than in the 45-min rest condition (109 +/- 14 beats/min vs 94 +/- 21 beats/min, P < .05). CONCLUSIONS: A post-warm-up recovery time of 10 min rather than 45 min is more beneficial to 200-m swimming time-trial performance.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".