The effect of creatine monohydrate supplementation on sprint skating in ice-hockey players.
Bibliographic record
Abstract
AIM: Creatine monohydrate supplementation is beneficial for enhancing high-intensity exercise performance, especially activities that involve repeated sprints. Creatine monohydrate supplementation is common in ice-hockey players. The purpose of this study was to determine the effect of creatine monohydrate supplementation on sprint skating performance in Junior B and collegiate ice-hockey players. METHODS: Seventeen ice-hockey players were randomly assigned to receive creatine (0.3 g/kg body mass/day for 5 days) or placebo. Before and after supplementation players performed repeated sprints to exhaustion on a skating treadmill (repeated 10-s sprints; 30-s rest between sprints) while blood lactate was simultaneously collected. The time to exhaustion on the treadmill test was calculated as total amount of time, including partial intervals, before the player reached exhaustion. Players were also tested for peak torque and average power during knee extension/flexion (3 sets of 10 reps; 60-s rest between sets) on an isokinetic dynamometer at 60 degrees/s. RESULTS: The change in time to exhaustion from before to after supplementation averaged 20.6+/-7 s in the creatine group and 21.9+/-13 s in the placebo group, with no differences between groups. Likewise, there were no differences between groups for changes in isokinetic peak torque and average power. There were no differences between groups over time for blood lactate changes during the repeated sprints on the treadmill. CONCLUSIONS: We conclude that creatine was not effective for improving performance in these ice-hockey players.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".