How conflicted authors undermine the World Health Organization (WHO) campaign to stop all use of asbestos: spotlight on studies showing that chrysotile is carcinogenic and facilitates other non-cancer asbestos-related diseases
Bibliographic record
Abstract
The silicate mineral asbestos is categorized into two main groups based on fiber structure: serpentine asbestos (chrysotile) and amphibole asbestos (crocidolite, amosite, anthophyllite, tremolite, and actinolite). Chrysotile is used in more than 2 000 applications and is especially prevalent in the construction industry. Although its use is banned or restricted in more than 52 countries, an estimated 107 000 workers die from asbestos exposure each year, and approximately 125 million workers continue to be exposed. Furthermore, ambient exposures persist to which the public is exposed, globally. Today, the primary controversies regarding the use of asbestos are the potencies of different types of asbestos, as opposed whether or not asbestos causes morbidity and mortality. The asbestos industry has promoted and funded research based on selected literature, ignoring both clinical and scientific knowledge. In this piece, we highlight a prominent example of a conflicted publication that sought to undermine the World Health Organization (WHO) campaign to stop the use of all forms of asbestos, including chrysotile asbestos. Independent and rigorous scientific data provide sufficient evidence that chrysotile asbestos, like other forms of asbestos, is a cause of asbestos-related morbidity and premature mortality.
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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 | 0.057 | 0.215 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".