Dietary carbohydrate, glycemic index, glycemic load, and the risk of prostate cancer
Bibliographic record
Abstract
Hypothesis. A diet with high dietary GL or a high overall GI is associated with increased risk of prostate cancer. Methods. A nested case-control study within the Canadian Study of Diet Lifestyle and Health (CSDLH). We examined the association of GI, GL and carbohydrate intake with prostate cancer risk among 673 prostate cancer cases and a random sample of 1290 controls selected from the CSDLH. Diet was assessed by food frequency questionnaire. Results. We observed no association of overall GI, GL and carbohydrate intake with the risk of prostate cancer. The multivariate Odds Ratio (OR) for the highest quartile versus the lowest quartile were 0.94 (95% CI=0.66-1.32) for GL, 0.89 (95% CI=0.66-1.20) for overall GI and 1.04 (95% CI=0.61-1.78) for daily carbohydrate intake. Conclusion. Findings from this thesis do not support the hypothesis that a diet with high dietary GL or high overall GI is associated with increased risk of prostate cancer.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".