The Association Between Ready-to-Eat Cereal Consumption, Nutrient Intakes of the Canadian Population 12 Years and Older and Body Weight Measures: Results From a Nationally Representative Canadian Population
Bibliographic record
Abstract
Background: To examine the relationship between ready-to-eat (RTE) cereal consumption habits and body mass index (BMI) of a nationally representative sample of Canadians. Methods: Population-based survey of Canadians aged 12 years and older. Participants provided 7-day self-reported food diary records during the data collection period of October 2003 through September 2004. Height and weight of the respondents was also reported. Main outcome measures included frequency of RTE cereal consumption, Body Mass Index (BMI), and nutrient intakes. The sample population of 2926 aged 12 years and older was divided into three groups by frequency of RTE cereal consumption over the 7-day period: 0-1 serving, 2-3 servings and 4+ servings. Results: The RTE cereal intake ranged from 0 to greater than 8 servings over the 7 days. Males who consumed 4+ servings of RTE Cereal had significantly lower mean BMI measures than the ones who consumed 0-1 serving (P < 0.006). Significantly lower proportion of Canadians who consumed 4+ serving of RTE cereal were classified as overweight or obese than those who consumed 0-1 servings in seven days (p = 0.011). Higher cereal intake group also had favourable nutrient intake profiles than the lower cereal intake group and were more likely to meet micronutrient intake recommendations. Conclusion: Self-reported RTE cereal consumption is related to lower BMI and improved nutrient intake in Canadians aged 12 years and older.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".