Asbestos Fibre Concentrations in the Lungs of Brake Workers: Another Look
Bibliographic record
Abstract
OBJECTIVE: To reanalyse data on the lung content of asbestos fibres among brake mechanics. METHODS: I re-analysed data published by Butnor, Roggli and colleagues on the lung content of chrysotile and tremolite asbestos fibres among brake mechanics and controls. Statistics of the distributions were estimated by maximum likelihood to accommodate observations below the detection limit. Mean concentrations were compared by the t-test, bootstrap resampling and interval-censored survival methods. RESULTS: The mean concentrations of fibres were higher among the brake workers than the controls. The concentration of tremolite fibres was higher than the concentration of chrysotile, a pattern similar to that observed among Quebec chrysotile miners and millers. CONCLUSIONS: Re-analysis of published data does not support the interpretation that, in automotive brake repair workers with malignant mesothelioma, asbestos content is within the normal range. The alternative interpretation that brake mechanics have a greater than background burden of asbestos fibres, attributable to occupational exposure to dusts from friction products manufactured from Canadian chrysotile, appears more credible. This asbestos burden might be associated with an increased risk of asbestos-associated cancers.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.002 | 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".