Bibliographic record
Abstract
Using participants in the 1970-1972 Nutrition Canada Survey (NCS), a retrospective cohort study was conducted to assess the relationship between tea, as well as coffee, cola and alcohol, and the risk of developing prostate cancer. The mortality and cancer experience of male NCS participants aged 50-84 years was determined up to 31 December 1993. Among the 3400 survey participants included in the study, 145 developed prostate cancer. No association was observed between tea (predominantly black tea) intake and prostate cancer. Subjects who drank more than 500 ml of tea per day experienced virtually the same risk as those who reported no tea consumption (rate ratio (RR) 1.02, 95% confidence interval (CI) 0.62-1.65). Compared to those who reported no coffee drinking, men who averaged more than 250-ml per day experienced a 40% increase in risk (95% CI 0.84-2.32). Cola consumption was not associated with an increased risk of prostate cancer. Total alcohol consumption was not related to subsequent development of prostate cancer, although very moderate consumption of wine (< 10 g per day), relative to no consumption, showed an RR of 1.48 (95% CI 1.05-2.09). These data do not support an association between consumption of tea and prostate cancer risk.
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.
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) | 0.000 | 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".