Nutrient and Fiber Intake and Risk of Renal Cell Carcinoma
Bibliographic record
Abstract
This study examines the association between nutrient and fiber intake and the risk of renal cell carcinoma (RCC). Between 1994 and 1997 in 8 Canadian provinces, mailed questionnaires were completed by 1,138 incident, histologically confirmed cases of RCC and 5,039 population controls. Measurement included information on socioeconomic status, lifestyle habits, and diet. A 69-item food frequency questionnaire provided data on eating habits 2 yr before data collection. Odds ratios (ORs) and 95% confidence intervals were derived through unconditional logistic regression. Intakes of total fat, saturated fat, monounsaturated fat, trans-fat, and cholesterol were associated with the risk of RCC; the ORs for the highest vs. the lowest quartile were 1.67, 1.53 and 1.46, 1.31, and 1.48, respectively. The positive association was apparently stronger in women, overweight or obese, and never smokers. Sucrose was related to the risk of RCC. High fiber intake was inversely associated with RCC risk. No association was found with intake of total protein and polyunsaturated fat, n-3 and n-6 polyunsaturated fatty acids, and total carbohydrates. The results were consistent across strata of sex, tobacco, and BMI. The findings suggest that a diet low in fats and cholesterol and rich in fiber could favorably affect the risk of RCC.
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 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) | 0.000 | 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 teacher head, 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".