On-ice sweat rate, voluntary fluid intake, and sodium balance during practice in male junior ice hockey players drinking water or a carbohydrate–electrolyte solution
Bibliographic record
Abstract
This study evaluated the repeatability of hydration and sweat measurements taken during on-ice hockey practices with players drinking only water, and determined whether having only a carbohydrate-electrolyte solution (CES) to drink during practices decreased fluid intake or affected other hydration and (or) sweat measures. All testing was conducted on elite players of an Ontario Hockey League team (+/-SE; mean age, 17.6 +/- 0.3 years; mean height, 182.9 +/- 1.4 cm; mean body mass, 83.0 +/- 1.7 kg). Players were studied 3 times over the course of 6 weekly on-ice practices (+/-SE; mean playing time, 1.58 +/- 0.07 h; mean temperature, 11.4 +/- 0.8 degrees C; mean relative humidity, 52% +/- 3%). There was strong repeatability of the measured hydration and sweat parameters between 2 similar on-ice practices when players drank only water. Limiting the players to drinking only a CES (as opposed to water) did not decrease fluid intake during practice (+/-SE; mean CES intake, 0.72 +/- 0.07 L.h-1 vs. mean water intake, 0.82 +/- 0.08 L.h-1) or affect sweat rate (1.5 +/- 0.1 L.h-1 vs. 1.5 +/- 0.1 L.h-1), sweat sodium concentration (72.4 +/- 5.6 mmol.L-1 vs. 73.0 +/- 4.4 mmol.L-1), or percent body mass loss (1.1% +/- 0.2% vs. 0.9% +/- 0.2%). Drinking a CES also improved sodium balance (-2.1 +/- 0.2 g.h-1 vs. -2.6 +/- 0.3 g.h-1) and provided the players with a significant carbohydrate (43 +/- 4 g.h-1 vs. 0 +/- 0 g.h-1) during practice. In summary, a single field sweat test during similar on-ice hockey practices in male junior hockey players is sufficient to evaluate fluid and electrolyte balance. Also, a CES does not affect voluntary fluid intake during practice, compared with water, in these players. The CES provided some salt to offset the salt lost in sweat, and carbohydrate, which may help maintain physical and mental performance in the later stages of practice.
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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 | 0.002 |
| 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) | 0.001 | 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".