Childhood obesity: food, nutrient, and eating-habit trends and influences
Bibliographic record
Abstract
The need has never been greater to support healthy eating and physical activity in children and youth; the numbers of overweight and obese children have doubled and tripled, respectively, over the past 3 decades. Poor eating habits, including inadequate intake of vegetables, fruit, and milk, and eating too many high-calorie snacks, play a role in childhood obesity. Grain products provide the highest percentage (31%) of daily calories, followed by "other foods," which have limited nutritional value (22% of daily calories). Snacks account for 27% of total daily calories, which is more than the calories consumed at breakfast (18%) and lunch (24%), but not dinner (31%). For Canadians older than 4 years of age, more than 41% of daily snack calories come from other foods, such as chips, chocolate bars, soft drinks, fruit drinks, sugars, syrup, preserves, fats, and oils. Habits that protect against childhood obesity include eating more vegetables and fruit, eating meals with family, and being physically active. Children's food habits and choices are influenced by family, caregivers, friends, schools, marketing, and the media. Successful interventions for preventing childhood obesity combine family- and school-based programs, nutrition education, dietary change, physical activity, family participation, and counseling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".