In-Season Creatine Supplementation by Rugby Union Football Players
Bibliographic record
Abstract
2303 Rugby union football is a sport that relies on muscular strength and endurance, as well as aerobic endurance. Simultaneous training for strength and aerobic endurance is challenging because one type of training can interfere with the other (i.e. heavy aerobic training can compromise muscle mass and strength development; whereas heavy strength training can compromise aerobic endurance due to muscle hypertrophy). PURPOSE: To determine if creatine supplementation during a season of rugby union football can preserve lean tissue mass and muscular performance, without negatively affecting aerobic endurance. METHODS: Rugby union football players were randomized to receive 0.1 g/kg/d creatine monohydrate (n = 9) or placebo (n = 9) during 8 weeks of the rugby season. Players practiced (mainly aerobic training) twice per week for approximately 2 hours per session and played one 80 minute game per week. Before and after the 8 weeks players were measured for body composition (air displacement plethysmography), muscular performance (number of repetitions at approximately 75% 1-RM for bench press and leg press), and aerobic endurance (Leger shuttle-run test with 1 minute stages of progressively increasing speed). RESULTS: There were time main effects for loss of body mass (−0.7 kg; p = 0.05), loss of fat mass (−1.9 kg; p<0.05) and a trend for an increase in lean tissue mass (+1.2 kg; p = 0.07), with no differences between groups. The group receiving creatine supplementation had a greater increase in the number of repetitions for combined bench press and leg press tests compared to the placebo group (+5.8 repetitions vs. +0.9 repetitions; p<0.05). There were no changes in either group for aerobic endurance. CONCLUSION: Creatine supplementation during a rugby union football season is effective for increasing muscular performance, but has no effect on body composition or aerobic endurance. Supported by NutraSense Co.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".