Sweat rate, salt loss, and fluid intake during an intense on-ice practice in elite Canadian male junior hockey players
Bibliographic record
Abstract
Previous research in many sports suggests that losing ~1%-2% body mass through sweating impairs athletic performance. Elite-level hockey involves high-intensity bursts of skating, arena temperatures are >10 degrees C, and players wear protective equipment, all of which promote sweating. This study examined the pre-practice hydration, on-ice fluid intake, and sweat and sodium losses of 44 candidates for Canada's junior men's hockey team (mean +/- SE age, 18.4 +/- 0.1 y; height, 184.8 +/- 0.9 cm; mass, 89.9 +/- 1.1 kg). Players were studied in groups of 10-12 during 4 intense 1 h practices (13.9 degrees C, 66% relative humidity) on 1 day. Hydration status was estimated by measuring urine specific gravity (USG). Sweat rate was calculated from body mass changes and fluid intake. Sweat sodium concentration ([Na]) was analyzed in forehead sweat patch samples and used with sweat rate to estimate sodium loss. Over 50% of players began practice mildly hypohydrated (USG > 1.020). Sweat rate during practice was 1.8 +/- 0.1 L.h(-1) and players replaced 58% (1.0 +/- 0.1 L.h(-1)) of the sweat lost. Body mass loss averaged 0.8% +/- 0.1%, but 1/3 of players lost more than 1%. Sweat [Na] was 54.2 +/- 2.4 mmol.L(-1) and sodium loss averaged 2.26 +/- 0.17 g during practice. Players drank only water during practice and replaced no sodium. In summary, elite junior hockey players incurred large sweat and sodium losses during an intense practice, but 2/3 of players drank enough to minimize body mass loss. However, 1/3 of players lost more than 1% body mass despite ready access to fluid and numerous drinking opportunities from the coaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".