Dietary Carotenoid Intake and Colorectal Cancer Risk
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
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.
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