Total and specific fluid consumption as determinants of bladder cancer risk
Bibliographic record
Abstract
Abstract We pooled the data from 6 case‐control studies of bladder cancer with detailed information on fluid intake and water pollutants, particularly trihalomethanes (THM), and evaluated the bladder cancer risk associated with total and specific fluid consumption. The analysis included 2,729 cases and 5,150 controls. Odds ratios (OR) and 95% confidence intervals (CI) for fluid consumption were adjusted for age, gender, study, smoking status, occupation and education. Total fluid intake was associated with an increased risk of bladder cancer in men. The adjusted OR for 1 l/day increase in intake was 1.08, (95% CI 1.03–1.14, p‐value for linear trend <0.001), while no trend was observed in women (OR = 1.04, 0.94–1.15; p‐value = 0.7). OR was 1.33 (1.12–1.58) for men in the highest category of intake (>3.5 l/day) as compared to those in the lowest (≤2 l/day). An increased risk was associated with intake of tap water. OR for >2 l/day vs. ≤0.5 l/day was 1.46 (1.20–1.78), with a higher risk among men (OR = 1.50, 1.21–1.88). No increased risk was observed for the same intake groups of nontap water in men (OR = 0.97, 0.77–1.22) or in women (OR = 0.85, 0.50–1.42). Increased bladder cancer risks were observed for an intake of >5 cups of coffee daily vs. <5 and for THM exposure, but neither exposure confounded or modified the OR for tap water intake. The association of bladder cancer with tap water consumption, but not with nontap water fluids, suggests that carcinogenic chemicals in tap water may explain the increased risk. © 2005 Wiley‐Liss, Inc.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".