Exposure to titanium dioxide, carbon black and cosmetic talc and risk of lung cancer: results from two case-control studies in Montreal
Bibliographic record
Abstract
71 Abstract: International Agency for Research on Cancer (IARC) recently evaluated the carcinogenicity of three poorly soluble low-toxic substances: carbon black, cosmetic talc or titanium dioxide. Though there is sufficient evidence of carcinogenity in experimental animals for these substances, the evidence in humans is sparse and equivocal. In the context of two large population based case-control studies of lung cancer carried out in Montreal, we are able to study the possible relationships between the exposure to each of carbon black, cosmetic talc or titanium dioxide and subsequent risk of lung cancer. Interviews for Study I were conducted in 1979-86 (857 cases, 533 population controls, 1349 cancer controls) and interviews for Study II were conducted in 1996-2001 (1236 cases and 1512 controls). Detailed lifetime job histories were elicited, and a team of hygienists and chemists evaluated the evidence of exposure to a host of occupational substances, including carbon black, cosmetic talc, and titanium dioxide. Lung cancer risk was analyzed in relation to each exposure, adjusting for several potential confounders, including smoking in a three-variable parameterization. For all three substances, in both sexes, the estimated odds ratios were close to the null value, with none significantly elevated. Our results support the hypothesis that exposure to carbon black, cosmetic talc, or titanium dioxide are not risk factors for lung cancer in humans. The results corroborate the recent evaluations of the IARC Monographs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".