The effects of dairy intake among preschool aged girls and boys on their weight status
Bibliographic record
Abstract
Intakes of milk and alternatives may affect body weight, but their associations with weight status in preschool aged children are unclear. This study assessed whether gender differences exist among milk intakes and if milk intake is related to body mass index‐for‐age z‐score (BAZ) in 483 children (3.74 ± 1.00 y) from Montreal, QC. Dietary intakes were assessed by direct observation at daycares and by telephone recalls to caregivers. At daycares, height and weight were measured. According to BAZ, 28% were classified as overweight/obese with no gender differences [total: boys (n=257); girls (n=230); (BAZ p=0.648)]. Dietary intake did not differ between genders (mean for group 1490.64 ± 395.64 kcal/d [17% protein, 56% carbohydrate and 27 % fat]); however, girls consumed significantly higher servings of dairy/d (p=0.018) and dietary calcium (mg/d) (p=0.008) but not dietary vitamin D (ug/d) (p=0.143) compared to boys. As a group, BAZ and milk intake did not correlate (rho= 0.076, p= 0.096), however a positive correlation was seen in girls milk intake and BAZ (rho= 0.161, p=0.015), but not in boys. These preliminary results suggest that milk intake differs among genders. Future analyses should include other food groups and test their associations to BAZ, taking into account gender differences. Funded by Dairy Farmers of Canada.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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".