A preliminary study on assessment of lead exposure in competitive biathletes: and its effects on respiratory health
Bibliographic record
Abstract
Aim: In this preliminary study, we aimed to assess the blood lead level (BLL) in biathletes compared to cross-country skiers, and to look at the effects on airway function, responsiveness, allergic sensitization and the report of training-induced respiratory symptoms. Methods: Eleven biathletes (19 ± 2 years old, sex: 6M:4F) and 12 cross-country skiers (18 ± 3 years old, sex: 4M:8F) had a blood sample, spirometry, bronchial provocation test to Methacholine, skin prick tests, and induced sputum. Biathletes performed the tests within 3 h after a 90 to 120 min shooting session (150 ± 45 bullets fired). Results: Lung function, airway responsiveness, sensitization to common airborne allergens, and the report of training-induced respiratory symptoms were not different between both groups of winter sport athlete. BLL was significantly higher in biathletes vs. cross-country skiers (geometric mean [95%CI]: 2.15 [1.37–2.94] μg/dL vs. 0.85 [0.81–0.89] μg/dL, respectively, p < 0.001, Cohen’s d = 1.25). One biathlete had a BLL greater than the recommended threshold (> 5 μg/dL). Significant correlations were observed in biathletes only between BLL and FEV1 and FVC in absolute value (r = 0.69, p = 0.02 and r = 0.69, p = 0.02, respectively). Conclusion: Despite higher BLL in biathletes, no difference in atopy, respiratory function or symptoms was observed with cross-country skiers in our experimental conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".