Effects of acute postexercise chocolate milk consumption during intensive judo training on the recovery of salivary hormones, salivary SIgA, mood state, muscle soreness, and judo-related performance
Bibliographic record
Abstract
This study examined the effects of postexercise chocolate milk (CM) or water (W) consumption during 5 days of intensive judo training with concomitant weight loss on salivary cortisol and testosterone, salivary secretory immunoglobulin A (SIgA), delayed-onset muscle soreness (DOMS), and judo-related performance. Twelve trained male judo athletes engaged in 5 days of intensive judo training followed by a simulated judo competition, on 2 separate training weeks 14 days apart. The athletes consumed 1000 mL of W (week 1) or CM (week 2) immediately post-training. During both weeks, athletes were instructed to "make weight" for the upcoming competition. Performance in timed push-ups and the Special Judo Fitness Test improved by 14.6% and 6.8%, respectively, at the end of the training week with CM consumption (both p < 0.001). Decreased salivary cortisol (p < 0.01) and a trend for an increased salivary testosterone/cortisol ratio (p = 0.07) were also observed midweek in the CM condition. Saliva flow rate was higher during the week with CM intake compared with W intake (p < 0.001). DOMS (p < 0.001) and mood disturbance (p < 0.0001) increased after the first day of training in the W condition but not in the CM condition. Salivary testosterone and SIgA responses were similar between treatments (p > 0.05). Body mass decreased by 1.9% in the W condition and by 1.1% in the CM condition, with no significant difference between treatments. This study indicates that postexercise CM consumption during short-term intensive judo training enhances aspects of recovery without affecting intentional weight loss.
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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 | 0.000 | 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) | 0.001 | 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".