Pulmonary mineral fibers after occupational and environmental exposure to asbestos in the Russian chrysotile industry
Bibliographic record
Abstract
BACKGROUND: As an indicator of occupational, domestic, and environmental exposure, the level and type of asbestos fibers were determined from lung tissue samples of workers and residents who resided in the area of the world's largest asbestos mine at Asbest, Russia. METHODS: Electron microscopy was used to analyze and measure the concentration of asbestos fibers in a series of 47 autopsies at the Asbest Town Hospital. Work histories were obtained from pathology reports and employment records. RESULTS: In 24 chrysotile miners, millers, and product manufacturers, the pulmonary concentrations of retained fibers (over 1 microm in length) were 0. 8-50.6 million f/g for chrysotile, and < 0.1-1.9 million f/g for amphiboles (tremolite and anthophyllite). The concentrations were lower in 23 persons without any known occupational contact with asbestos; 0.1-14.6 million f/g for chrysotile, and < 0.1-0.7 million f/g for amphiboles. On average, 90% of all inorganic fibers were chrysotile, and 5% tremolite/anthophyllite. No amosite or crocidolite fibers were detected in any of the samples. CONCLUSIONS: The mean and range of pulmonary chrysotile concentrations were about the same as reported previously from the Canadian mining and milling industry. In the Russian samples, the mean concentration of tremolite fibers were less by at least one order of magnitude. Occupational contact was the most important source of asbestos exposure.
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) | 0.000 | 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 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".