Pneumoconiosis from Agricultural Dust Exposure among Young California Farmworkers
Bibliographic record
Abstract
BACKGROUND: Agricultural workers are exposed to airborne pollutants, including organic and inorganic (mineral) dusts. OBJECTIVES: Lung autopsy specimens from consecutive coroner's cases of Hispanic males in Fresno County, California, (n = 112) were obtained to determine whether mineral dust exposure in agricultural work leads to pneumoconiosis. METHODS: The left lung was fixed by inflation. We evaluated airway and parenchymal pathology using standardized diagnostic criteria and semiquantitative grading schemata, including the grading of small airways for fibrosis and birefringent mineral dust particles. We analyzed lung dust burden on a subset of 37 lungs following bleach digestion, using scanning electron microscopy (SEM), X-ray spectrometry (XRS) and image analysis, and by X-ray diffraction for crystalline silica (CSi). Farmworkers comprised 51.5% and nonfarmworkers 48.5% of the samples. RESULTS: Proximal airways demonstrated little mineral dust accumulation, but membranous and respiratory bronchioles had wall thickening, remodeling, and inflammation associated with carbonaceous and mineral dust deposition. These changes were independently associated with agricultural work, cigarette smoking, and increased age. Mineral dust small airways disease, pneumoconiosis (macules and nodules), and pathologic changes consistent with chronic bronchitis, emphysema, and interstitial fibrosis predominated in farmworkers compared with nonfarmworkers. CSi, determined gravimetrically, and aluminum silicate particles, determined by SEM/XRS, were increased in the lungs of farmworkers compared with nonfarmworkers and were significantly (p < 0.05) associated with small airway disease and pneumoconiosis. CONCLUSION: Mineral dust exposure is associated with increased small airway disease and pneumoconiosis among California farmworkers; however, the clinical significance and natural history of these changes remains to be determined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".