Dietary Carotenoid Intake and Colorectal Cancer Risk
Bibliographic record
Abstract
Several studies have found inverse associations between fruit and vegetable consumption and colorectal cancer risk, suggesting the potential etiological importance of carotenoids (and other phytochemicals) contained in these foods. However, only one study (a case-control study) has examined the association between dietary carotenoids other than beta-carotene and colorectal cancer risk. In the study reported here, we examined the relationships between dietary intakes of beta-carotene, alpha-carotene, lycopene, lutein, and beta-cryptoxanthin and colorectal cancer risk in a large cohort study of Canadian women. A case-cohort analysis was undertaken within the cohort of 56,837 women who were enrolled in the Canadian National Breast Screening Study and who completed a self-administered dietary questionnaire. During follow-up to the end of 1993, a total of 388 women were diagnosed with colorectal cancer. For comparative purposes, a subcohort of 5,681 women was randomly selected. After exclusions for various reasons, the analyses were based on 295 cases and 5,334 noncases. We did not find any clear association between intake of any of the studied carotenoids and colorectal cancer risk in the study population as a whole or in subgroups defined by smoking status, relative body weight (body mass index), intakes of total fat, energy, alcohol, and folic acid, or menopausal status. Our data do not support any association between dietary intakes of the studied carotenoids and colorectal cancer risk. However, given that this is the first prospective cohort study of carotenoids in relation to colorectal cancer, further studies are warranted.
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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) | 0.000 | 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) | 0.001 | 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".