Effects of caffeine and carbohydrate mouth rinses on repeated sprint performance
Bibliographic record
Abstract
Our purpose was to examine the effectiveness of carbohydrate and caffeine mouth rinses in enhancing repeated sprint ability. Previously, studies have shown that a carbohydrate mouth rinse (without ingestion) has beneficial effects on endurance performance that are related to changes in brain activity. Caffeine ingestion has also demonstrated positive effects on sprint performance. However, the effects of carbohydrate or caffeine mouth rinses on intermittent sprints have not been examined previously. Twelve males performed 5 × 6-s sprints interspersed with 24 s of active recovery on a cycle ergometer. Twenty-five milliliters of either a noncaloric placebo, a 6% glucose, or a 1.2% caffeine solution was rinsed in the mouth for 5 s prior to each sprint in a double-blinded and balanced cross-over design. Postexercise maximal heart rate and perceived exertion were recorded, along with power measures. A second experiment compared a combined caffeine-carbohydrate rinse with carbohydrate only. Compared with the placebo mouth rinse, carbohydrate substantially increased peak power in sprint 1 (22.1 ± 19.5 W; Cohen's effect size (ES), 0.81), and both caffeine (26.9 ± 26.9 W; ES, 0.71) and carbohydrate (39.1 ± 25.8 W; ES, 1.08) improved mean power in sprint 1. Experiment 2 demonstrated that a combination of caffeine and carbohydrate improved sprint 1 power production compared with carbohydrate alone (36.0 ± 37.3 W; ES, 0.81). We conclude that carbohydrate and (or) caffeine mouth rinses may rapidly enhance power production, which could have benefits for specific short sprint exercise performance. The ability of a mouth-rinse intervention to rapidly improve maximal exercise performance in the absence of fatigue suggests a central mechanism.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".