Occupational asthma and allergy in snow crab processing in Newfoundland and Labrador
Bibliographic record
Abstract
BACKGROUND: Risk factors and prevalence of occupational asthma (OA) and occupational allergy (OAl) in the snow crab-processing industry have been poorly studied. OBJECTIVE: To estimate the prevalence of OA and OAl in snow crab-processing workers and determine their relationship with exposure to snow crab allergens and other potential risk factors. METHODS: A total of 215 workers (120 female/95 male) were recruited from four plants in Newfoundland and Labrador, Canada in 2001-2002. Results from questionnaires, skin-prick tests to snow crab meat and cooking water, specific IgEs against the latter, spirometry and peak flow monitoring were used to develop a diagnostic algorithm. An index based on work history and exposure measurements of snow crab aeroallergens was developed to estimate the cumulative exposure for each worker. RESULTS: The prevalences of almost certain or highly probable OA and OAl were 15.8% and 14.9%, respectively. A high cumulative exposure to crab allergens, in jobs mostly held by women, was associated with OA (odds ratio (OR) = 14.0, 95% CI 3.0 to 65.8) (highest vs lowest Cumulative Exposure Index) and with OAl (OR = 7.1, 95% CI 1.9 to 29.0); job held when symptoms started (cleaning, packing, freezing) also predicted OA (OR = 3.9, 95% CI 1.6 to 8.7) and OAl (OR = 3.2, 95% CI 1.4 to 7.5). Atopy (OR = 2.8, 95% CI 1.2 to 6.8), female gender (OR = 10.7, 95% CI 3.6 to 32.1) and smoking were significant determinants for OA (OR = 3.1, 95% CI 1.3 to 7.4). CONCLUSIONS: The prevalences of OA and OAl are high in snow crab-processing workers of Canada's East Coast. Cumulative exposure to snow crab allergens was related to the prevalences of OA and OAl in a dose-response manner taking into account atopy, gender and smoking.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".