Respiratory Ill‐Health and Welding Exposures: A Canadian Cohort Study
Bibliographic record
Abstract
ABSTRACT Introduction Respiratory ill‐health in welders is well documented but without a clear indication of exposures responsible. Methods In a Canadian cohort study of welders and electrical workers, we collected self‐reports of asthma/wheeze and rhinitis at each 6‐monthly contact for up to 5 years. Physician diagnoses of asthma and chronic obstructive pulmonary disease (COPD/bronchitis) were extracted from the Alberta administrative health database (AHDB). Welders provided task‐specific information at each contact. Estimates were derived for cumulative exposure to particulates, chromium, and nickel. Factors associated with time to first and recurrent events were identified by proportional hazards regression, adjusting for sex, age, and smoking. Results Of 1001 welders and 884 workers in electrical trades recruited, 1338 in Alberta were matched to the AHDB. Welders were more at risk of physician‐diagnosed COPD/bronchitis than those in the electrical trades (HR for first report = 1.87; 95% CI = 1.27–2.77) but not of asthma. Times to first self‐report of asthma/wheezing (HR = 1.58; 95% CI = 1.23–2.04) and rhinitis (HR = 1.29; 95%CI = 1.11–1.49) were shorter in welders. Among welders, time to physician‐diagnosed asthma was weakly related to cumulative nickel exposure (mg/m3_h/100) (HR = 1.08; 95% CI = 1.00–1.17). COPD/bronchitis was related to cumulative exposure to total dust (g/m3_h) (HR = 1.01; 95% CI = 1.00–1.03) and to chromium (mg/m3_h/100) (HR = 1.14; 95% CI = 1.04–1.26). The risk of both asthma and COPD/bronchitis reduced with time using local exhaust ventilation. Self‐reported rhinitis increased with cumulative nickel exposure (HR = 1.00; 95% CI = 1.00–1.01). Conclusions Welders were at increased risk of COPD/bronchitis, with risk related to cumulative dust and chromium exposure. Nickel exposure increased the risk of asthma and rhinitis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".