Postexercise rehydration: potassium-rich drinks versus water and a sports drink
Bibliographic record
Abstract
Fluid retention, thirst quenching, tolerance, and palatability of different drinks were assessed. On 4 different days, 12 healthy, physically active volunteers (24.4 ± 3.2 years old, 74.75 ± 11.36 kg body mass (mean ± S.D)), were dehydrated to 2.10% ± 0.24% body mass by exercising in an environmental chamber (32.0 ± 0.4 °C dry bulb, 53.8 ± 5.2% relative humidity). Each day they drank 1 of 4 beverages in random order: fresh coconut water (FCW), bottled water (W), sports drink (SD), or potassium-rich drink (NEW); volume was 120% of weight loss. Urine was collected and perceptions self-reported for 3 h. Urine output was higher (p < 0.05) for W (894 ± 178 mL) than SD (605 ± 297 mL) and NEW (599 ± 254 mL). FCW (686 ± 250 mL) was not different from any other drink (p > 0.05). Fluid retention was higher for SD than W (68.2% ± 13.0% vs. 51.3% ± 12.6%, p = 0.013), but not for FCW and NEW (62.5% ± 15.4% and 65.9% ± 15.4%, p > 0.05). All beverages were palatable and well tolerated; none maintained a positive net fluid balance after 3 h, but deficit was greater in W versus SD (p = 0.001). FCW scored higher for sweetness (p = 0.03). Thirst increased immediately after exercise but returned to baseline after drinking a small volume (p < 0.0005). In conclusion, additional potassium in FCW and NEW did not result in additional rehydration benefits over those already found in a conventional sports drink with sodium.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".