Coal mine dust lung disease in miners killed in the Upper Big Branch disaster: a review of lung pathology and contemporary respirable dust levels in underground US coal mines
Bibliographic record
Abstract
Objectives In 2010, 29 coal miners died due to an explosion at the Upper Big Branch (UBB) mine in West Virginia, USA. Autopsy examinations of 24 individuals with evaluable lung tissue identified 17 considered to have coal workers’ pneumoconiosis (CWP). The objectives of this study were to characterise histopathological findings of lung tissue from a sample of UBB fatalities and better understand the respirable dust concentrations experienced by these miners at UBB relative to other US coal mines. Methods Occupational pulmonary pathologists evaluated lung tissue specimens from UBB fatalities for the presence of features of pneumoconiosis. Respirable dust and quartz samples submitted for regulatory compliance from all US underground coal mines prior to the disaster were analysed. Results Families of seven UBB fatalities provided consent for the study. Histopathologic evidence of CWP was found in all seven cases. For the USA, central Appalachia and UBB, compliance dust samples showed the geometric mean for respirable dust was 0.468, 0.420 and 0.518 mg/m 3 , respectively, and respirable quartz concentrations were 0.030, 0.038 and 0.061 mg/m 3 . After adjusting for quartz concentrations, UBB exceeded the US permissible exposure limit (PEL) for respirable dust in 28% of samples. Conclusions Although higher than average respirable dust and quartz levels were observed at UBB, over 200 US underground coal mines had higher dust concentrations than UBB and over 100 exceeded the PEL more frequently. Together with lung histopathological findings among UBB fatalities, these data suggest exposures leading to CWP in the USA are more prevalent than previously understood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".