Anaerobic performance when rehydrating with water or commercially available sports drinks during prolonged exercise in the heat
Bibliographic record
Abstract
The effects that rehydrating drinks ingested during exercise may have on anaerobic exercise performance are unclear. This study aimed to determine which of four commercial rehydrating drinks better maintains leg power and force during prolonged cycling in the heat. Seven endurance-trained and heat-acclimatized cyclists pedaled for 120 min at 63% maximum oxygen consumption in a hot, dry environment (36 degrees C; 29% humidity, 1.9 m.s-1 airflow). In five randomized trials, during exercise, subjects drank 2.4 +/- 0.1 L of (i) mineral water (WAT; San Benedetto), (ii) 6% carbohydrate-electrolyte solution (Gatorade lemon), (iii) 8% carbohydrate-electrolyte solution (Powerade Citrus Charge), (iv) 8% carbohydrate-electrolyte solution with lower sodium concentration than other sports drinks (Aquarius orange), or (v) did not ingest any fluid (DEH). Fluid balance, rectal temperature (Trec), maximal cycling power (Pmax), and leg maximal voluntary isometric contraction (MVC) were measured. During DEH, subjects lost 3.7 +/- 0.2% of initial body mass, whereas subjects lost only 0.8% +/- 0.1% in the other trials (p < 0.05). Final Trec was higher in DEH than in the rest of the trials (39.4 +/- 0.1 degrees C vs. 38.7 +/- 0.1 degrees C; p < 0.05). Pmax was similar among all trials. Gatorade and Powerade preserved MVC better than DEH (-3.1% +/- 2% and -3.8% +/- 2% vs. -11% +/- 2%, p < 0.05), respectively, whereas WAT and Aquarius did not (-6% +/- 2%). Compared with DEH, rehydration with commercially available sports drinks during prolonged exercise in the heat preserves leg force, whereas rehydrating with water does not. However, low sodium concentration in a sports drink seems to preclude its ergogenic effects on force.
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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) | 0.001 | 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 | 0.000 | 0.000 |
| 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".