Food, Beverage, and Macronutrient Intakes in Postmenopausal Caucasian and Chinese-Canadian Women
Bibliographic record
Abstract
International differences in breast cancer rates and diet, and studies in migrants, suggest that diet may be a modifiable risk factor for breast cancer. The goal of this cross-sectional study was to examine the dietary intakes of women from populations considered to be at different risks for breast cancer. We collected four 24-h food recalls in 3 groups of postmenopausal Canadian women: Caucasians (n = 392), Chinese women born in the West or who migrated to the West before age 21 (n = 156), and recent Chinese migrants (n = 383). Compared to Caucasians, recent Chinese migrants had lower energy and fat intakes and higher protein and carbohydrate intakes. Recent Chinese migrants consumed higher amounts of grains, vegetables, fish, and soy and lower amounts of alcohol, meat, dairy products, and sweets than Caucasians. Western-born Chinese and early Chinese migrants had intakes intermediate between the other 2 groups. The differences in intake between the ethnic groups suggest foods and nutrients that may contribute to the differences in risk of breast cancer between women in Canada and China. Future work will examine whether these dietary differences are associated with biological markers of breast cancer risk.
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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 | 0.002 |
| Science and technology studies | 0.002 | 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".