Bibliographic record
Abstract
Sarcoidosis is an important member of the family of granulomatous lung diseases. Since its recognition in the late 19th century, sarcoidosis has been thought of as a disease of unknown cause. Over the past 20 years, this paradigm has been shifting, more rapidly in the past 10 years. Epidemiologic studies, bolstered by case reports, have provided evidence of causal associations between occupational exposure to specific agents and sarcoidosis. Pathogenesis has been more clearly defined, including the role of gene-exposure interactions. The use of in vitro lymphocyte proliferation testing to detect sensitization to inorganic antigens is being examined in patients with sarcoidosis. These antigens include silica and certain metals. Results of studies to date show differences in immunoreactivity of occupationally exposed sarcoidosis cases compared with control cases, suggesting that lymphocyte proliferation testing may prove useful in diagnosing work-related disease. This review discusses recently published findings regarding associations between occupational exposure to silica and silicates, World Trade Center dust, and metals and risk for sarcoidosis, as well as advances in the development of diagnostic tools. Not all cases of sarcoidosis have an identified cause, but some do. Where the cause is occupational, its recognition is critical to enable effective treatment through removal of the affected worker from exposure and to inform intervention aimed at primary prevention.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".