Airway inflammation, cough and athlete quality of life in elite female cross‐country skiers: A longitudinal study
Bibliographic record
Abstract
The aim of this study was to investigate the effect of a season of cross-country training and racing on airway inflammation, cough symptoms, and athlete quality of life in female skiers. Eighteen elite female skiers performed sputum induction and completed the Leicester Cough Questionnaire (LCQ) and the Recovery-Stress Questionnaire (REST-Q) at three time points (T1 - May/Jun, T2 - Oct/Nov, T3 - Jan-Mar) during the year. No changes were observed between T1 and T2. However, an increase in sputum eosinophils and lymphocytes (P < 0.05) and a significant change in all three domains of the LCQ were observed between T1 and T3 (P < 0.05). A significant association was found between the total yearly hours of training and the change in the total cell count (r(2) = 0.74; P = 0.006), and a number of other sputum cell counts between T1 and T3. No changes were observed for any domain of the REST-Q. The results of this study demonstrate that airway inflammation and cough symptoms are significantly increased in elite female cross-country skiers across a year of training and racing. The increase in airway inflammation is related to the total amount of training and is worse during the winter months when athletes are training and racing in cold, dry air.
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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 | 0.001 | 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 | 0.001 |
| 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".