Influence of multiple cross-country ski races on respiratory function and symptoms in cross-country skiers
Bibliographic record
Abstract
Objectives This study studied how multiple cross-country ski races affect respiratory function and symptoms in different age groups. Methods Eighteen ≥ 19 and 18 ≤ 18 years of age skiers performed morning spirometry , post-race/training spirometry and recorded respiratory symptoms daily over a National Championship (baseline day, 3 races and 2 training days). Results Races decreased resting spirometry and a rest day increased spirometry in both groups. Overall resting maximal mean decline was 4.6 ± 8.8%; 2.5 ± 8.2% for forced expiratory flow in 1 second (FEV 1 ) and 6.3 ± 2.7%; 4.5 ± 2.7% forced vital capacity (FVC) in ≥ 19 and ≤ 18 aged skiers respectively. FEV 1 decreased in 50% of skiers post-race, mean symptoms were 3.3 ± 0.5 (≤ 18 yrs); and 2.5 ± 0.5 (≥ 19 yrs). Post-race cough (86%) was most common symptom. Conclusions Multiple races reduced resting function, especially FVC in both age groups. Greater cough and decreased function in FEV 1 pre-post-race in older skiers indicate potential age-related change. This study is the first to show how multiple ski races affect respiratory function and symptoms cumulatively.
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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 | 0.001 |
| 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".