The Role of Selected Dietary Factors in the Etiology of Sporadic Colorectal Cancer: Results from a Population-Based Case-Control Study
Bibliographic record
Abstract
Colorectal cancer (CRC) is the third most common type of cancer in Canada. Some dietary factors have been identified for the prevention of CRC; however, the effect of consuming fish, fruit, non-starchy vegetables, coffee, or tea remains unclear. The associations between these dietary variables and CRC were investigated using 346 cases and 309 controls from the COLDENT case-control study. To incorporate duration and intensity of consumption, a measure of serving-years/cup-years was used. Multivariable logistic regression was used and included many covariates for adjustment. Associations of cumulative fish, fruit, non-starchy vegetable, coffee, and tea consumption with CRC were almost null. Results for recent past, distant past, and very distant past consumption categories were also close to null. Considering the potential for bias, the results suggest that the true association between these dietary exposures and CRC is not very strong.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".