Agricultural Dust Exposure and Respiratory Symptoms Among California Farm Operators
Bibliographic record
Abstract
OBJECTIVE: To study whether dust exposure in California agriculture is a risk factor for respiratory symptoms. METHODS: A population-based survey of 1947 California farmers collected respiratory symptoms, occupational and personal exposures. Associations between dust and respiratory symptoms were assessed by logistic regression models. RESULTS: The prevalence of persistent wheeze was 8.6%, chronic bronchitis 3.8%, chronic cough 4.2%, and asthma 7.8%. Persistent wheeze was independently associated with dust in a dose-response fashion odds ratio, 1.2 (95% confidence interval[CI]=0.8-2.0) and 1.8 (95% CI=1.1-3.2) for low and high time in dust. A borderline significant association between chronic bronchitis and dust exposure was found. Asthma was associated with keeping livestock, but not with dust exposure. CONCLUSIONS: Occupational dust exposure among California farmers, only one third of whom tended animals, was independently associated with chronic respiratory symptoms.
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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".