Thermoregulatory responses in elite cross-country skiers during international competitions and training
Bibliographic record
Abstract
Background: The aim of this study was to describe the thermoregulatory responses of elite athletes during competitions and training of the international cross-country skiing FIS Scandinavian Cup in Finland, held under cold (subzero) ambient conditions. Methods: The core and skin temperatures were continuously recorded during two competition formats-a 10-km race (n = 18; 10 m, 8 f) and a 20-km race (n = 14; 9 m, 5 f)-and during training (n = 11; 7 m, 4 f) using electronic temperature pills and temperature sensors fixed on the chest, arm, hand, and thigh, respectively. The heart rate and skiing speed were continuously recorded using heart rate monitors with integrated GPS technology. Ambient temperatures during the measuring period ranged from -13.0 °C to -1.3 °C. Results: ) increased significantly during the 10-km classic (39.0 °C ± 0.4 °C) and the 20-km freestyle (39.2 °C ± 0.7 °C) races (all p < 0.001) and during trainings (38.3 °C ± 0.5 °C). In contrast, skin temperature decreased in all four body parts (all p < 0.001), with the greatest decreases measured on the thigh [18.7 °C ± 4.1 °C (10-km race), 20.7 °C ± 4.6 °C (20-km race), and 18.5 °C ± 3.2 °C (training)]. During both races, the heart rate significantly increased over time while the racing speed decreased (p < 0.001, respectively). The mean skin temperature of the thigh correlated with skiing speed in the 10-km (r = 0.573, p = 0.041) and the 20-km (r = 0.682, p = 0.021) races. Conclusion: In summary, despite low ambient temperatures under real competition and training conditions, the athletes exhibited high heat generation, which enabled them to maintain a high core temperature. In contrast, the skin temperature dropped sharply during competitions and trainings. The association between the low mean skin temperature and the lower racing speed should be investigated further.
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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) | 0.000 | 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) | 0.002 | 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".