Lung Disease Caused by Exposure to Coal Mine and Silica Dust
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Susceptible workers exposed to coal mine and silica dust may develop a variety of pulmonary diseases. The prime example is classical pneumoconiosis, a nodular interstitial lung disease that, in severe cases, may lead to progressive massive fibrosis (PMF) . Exposure to silica and coal mine dusts may also result in pulmonary scarring in a pattern that mimics idiopathic pulmonary fibrosis, and in chronic obstructive pulmonary disease (COPD), including emphysema and chronic bronchitis, that appears indistinguishable from obstructive lung disease caused by exposure to tobacco smoke. Coal mine and silica dust may therefore result in restrictive, obstructive, or mixed patterns of impairment on pulmonary function testing. Most physicians are aware of the nodular fibrosing pulmonary tissue reactions in response to retained dust, but they may not realize that these other reactions of the pulmonary parenchyma and airways to dust exist and can result in significant respiratory dysfunction in sensitive individuals. This article discusses current data on exposure to coal mine and silica dust in the United States, the epidemiology of the diseases caused by these exposures, and new concepts of causation and pathogenesis. We also review the patterns of pulmonary disease and impairment that may result.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it