Disinfection Byproducts and Bladder Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Exposure to disinfection byproducts in drinking water has been associated with an increased risk of bladder cancer. We pooled the primary data from 6 case-control studies of bladder cancer that used trihalomethanes as a marker of disinfection byproducts. METHODS: Two studies were included from the United States and one each from Canada, France, Italy, and Finland. Inclusion criteria were availability of detailed data on trihalomethane exposure and individual water consumption. The analysis included 2806 cases and 5254 controls, all of whom had measures of known exposure for at least 70% of the exposure window of 40 years before the interview. Cumulative exposure to trihalomethanes was estimated by combining individual year-by-year average trihalomethane level and daily tap water consumption. RESULTS: There was an adjusted odds ratio (OR) of 1.24 in men exposed to an average of more than 1 microg/L (ppb) trihalomethanes compared with those who had lower or no exposure (95% confidence interval [CI] = 1.09-1.41). Estimated relative risks increased with increasing exposure, with an OR of 1.44 (1.20-1.73) for exposure higher than 50 microg/L (ppb). Similar results were found with other indices of trihalomethane exposure. Among women, trihalomethane exposure was not associated with bladder cancer risk (0.95; 0.76-1.20). CONCLUSIONS: These findings strengthen the hypothesis that the risk of bladder cancer is increased with long-term exposure to disinfection byproducts at levels currently observed in many industrialized countries.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 it