Consumption of non-alcoholic beverages and prostate cancer risk
Bibliographic record
Abstract
Our objective was to investigate the relations between the consumption of coffee, tea and carbonated beverages and the development of prostate cancer. The design was a population-based case-control study set in Montreal. The analysis was restricted to the subset of men, aged 45-70 years, who underwent interviews in which aspects of lifelong consumption of non-alcoholic beverages were ascertained. There were 399 incident cases of prostate cancer, 476 population controls and 621 cancer controls. There was no association between the consumption of either coffee or carbonated beverages and the development of prostate cancer. Among daily tea drinkers, the odds ratio associated with the highest tertile of cumulative consumption was 2.0 (95% confidence interval (CI) 1.3-3.0) when using population controls and 1.6 (95% CI 1.0-2.4) when using cancer controls. In conclusion, the consumption of coffee or carbonated beverages does not influence the risk of prostate cancer. Our findings provide no support to the hypothesis that tea consumption may be protective. While tea consumption may increase prostate cancer risk, we were unable to rule out alternative explanations for the positive association that we observed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".