Pathology and Mineralogy of the Pneumoconioses
Bibliographic record
Abstract
Pneumoconioses represent the spectrum of lung diseases caused by inhalation of respirable particulate matter small enough (typically <5-µm diameter) to reach the terminal airways and alveoli. Pneumoconioses primarily occur in occupational settings where workers perform demanding and skilled manual labor including mining, construction, stone fabrication, farming, plumbing, electronics manufacturing, shipyards, and more. Most pneumoconioses develop after decades of exposure, though shorter latencies can occur from more intense particulate matter exposures. In this review, we summarize the industrial exposures, pathologic findings, and mineralogic features of various well-characterized pneumoconioses including silicosis, silicatosis, mixed-dust pneumoconiosis, coal workers' pneumoconiosis, asbestosis, chronic beryllium disease, aluminosis, hard metal pneumoconiosis, and some less severe pneumoconioses. We also review a general framework for the diagnostic work-up of pneumoconioses for pulmonologists including obtaining a detailed occupational and environmental exposure history. Many pneumoconioses are irreversible and develop due to excessive cumulative respirable dust inhalation. Accurate diagnosis permits interventions to minimize ongoing fibrogenic dust exposure. A consistent occupational exposure history coupled with typical chest imaging findings is usually sufficient to make a clinical diagnosis without the need for tissue sampling. Lung biopsy may be required when exposure history, imaging, and testing are inconsistent, there are unusual or new exposures, or there is a need to obtain tissue for another indication such as suspected malignancy. Close collaboration and information-sharing with the pathologist prior to biopsy is of great importance for diagnosis, as many occupational lung diseases are missed due to insufficient communication. The pathologist has a broad range of analytic techniques including bright-field microscopy, polarized light microscopy, and special histologic stains that may confirm the diagnosis. Advanced techniques for particle characterization such as scanning electron microscopy/energy dispersive spectroscopy may be available in some centers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".