Creatine Monohydrate Supplementation Enhances High-Intensity Exercise Performance in Males and Females.
Bibliographic record
Abstract
Creatine monohydrate supplementation has been shown to enhance high-intensity exercise performance in some but not all studies. Part of the controversy surrounding the ergogenic effect(s) of creatine monohydrate supplementation may relate to design issues that result in low statistical power. A further question that remains unresolved in the creatine literature is whether or not males and females respond in a similar manner to supplementation. We studied the effect of creatine supplementation upon high intensity exercise performance in 24 subjects (n = 12 males, n = 12 females). Creatine monohydrate (Cr; 5g, 4x/d 3 4d) and placebo (Pl; glucose polymer 3 4d) were provided using a randomized, double-blind crossover design (7 week washout). Outcome measures included: 2 3 30-s anaerobic cycle test, with plasma lactate pre- and post-test; dorsi-flexor: maximal voluntary contraction (MVC), 2-min fatigue test, and electrically stimulated peak and tetanic torque; isokinetic knee extension torque and 1-min ischemic handgrip strength. Significant main effects of Cr treatment included: increased peak and relative peak anaerobic cycling power ( 3.7%; p <. 05), dorsi-flexion MVC torque ( 6.6%; p <.05), and increased lactate ( 20.8%; p <.05) with no gender specific responses. We concluded that short-term Cr supplementation can increase indices of high-intensity exercise performance for both males and females.
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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 | 0.000 |
| 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) | 0.004 | 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".