Exposure to titanium dioxide and risk of lung cancer in a population-based study from Montreal
Bibliographic record
Abstract
OBJECTIVES: This study assessed the lung cancer risk from exposure to titanium dioxide, an important pigment with limited evidence of carcinogenicity in experimental animals but sparse data for humans. METHODS: The risk of lung cancer among residents in Montreal, Canada, was analyzed, including 857 histologically confirmed cases of lung cancer diagnosed during 1979-1985 among men aged 35-70 years and a group of referents comprising 533 randomly selected, healthy residents and 533 persons with cancer in organs other than the lung. Exposure to titanium dioxide and other titanium compounds was assessed by a team of industrial hygienists on the basis of a detailed occupational questionnaire. RESULTS: Thirty-three cases and 43 referents were classified as exposed to titanium dioxide. The odds ratio was 0.9 [95% confidence interval (95% CI) 0.5-1.5]. No trend was apparent according to the estimated frequency, level, or duration of exposure. The odds ratio was 1.0 (95% CI 0.3-2.7) for medium or high exposure for at least 5 years. Few subjects were classified as exposed to titanium dioxide fumes or to other titanium compounds, but the risk of lung cancer was nonsignificantly increased for exposure to these agents. CONCLUSIONS: Although misclassification of exposure and low exposure prevalence might have resulted in false negative results, this study does not suggest that occupational exposure to titanium dioxide increases the risk of lung cancer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".