Caffeine coingested with carbohydrate on performance recovery in national-level paddlers: a randomized, double-blind, crossover, placebo-controlled trial
Bibliographic record
Abstract
BACKGROUND: Caffeine enhances muscle glycogen resynthesis postexercise; however, the next-day effects on recovery are unknown. The present study aimed to examine the effects of carbohydrate (CHO) supplementation with or without caffeine (CAF) 24-h following exhaustive exercise on time trial performance in elite paddling athletes. METHODS: Nine highly trained male paddlers (21±2 y) completed three experimental trials in a randomized, double-blind, crossover manner. Following an exhaustive exercise session (20-km timed paddle) participants ingested: 1) 0.6 g/kg of carbohydrate (CHO); 2) 0.6 g/kg of carbohydrate with 6 mg/kg of caffeine (CAF+CHO); or 3) placebo (PLA), at four time-points (immediately after, and 2, 6, and 12-h postexercise) in addition to their typical dietary intake. After 24 h, 5 attempts of on-water 500-m paddling time-trial was performed, and the average time was recorded. Blood samples were taken at rest and following both the 20-km and the 5×500 m exercise to determine changes in plasma cortisol, insulin, and glucose. RESULTS: There was a significant main effect of condition (P<0.001), with post-hoc analysis revealing that both CHO conditions (CHO: 98.7±2.8 s, P=0.0003; CAF+CHO: 97.9±2.3 s, P=0.0002) were significantly faster compared to PLA (101.0±3.1 s); however, CAF did not augment time trial performance compared to CHO (P=0.16). There was no significant condition by time interactions for glucose, cortisol, or insulin before and after the 20-km depleting exercise and 500-m time trial. CONCLUSIONS: In elite male paddlers, CHO, independent of caffeine, enhanced time trial performance 24 hours following exhaustive exercise.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".