<i>Determinants of Diet Quality</i>Among Canadian Adolescents
Bibliographic record
Abstract
PURPOSE: Dietary intakes and nutrition behaviours were examined among different diet quality groups of Canadian adolescents. METHODS: This cross-sectional study included 2850 Alberta and Ontario adolescents aged 14 to 17, who completed a self-administered web-based survey that examined nutrient intakes and meal behaviours (meal frequency and meal consumption away from home). RESULTS: Mean macronutrient intakes were within Acceptable Macronutrient Distribution Ranges; however, micronutrient intakes and median food group intakes were below recommendations based on Canada's Food Guide to Healthy Eating (CFGHE). Overall diet quality indicated that 43%, 47%, and 10% of students had poor, average, and superior diet quality, respectively. Adolescents with lower diet quality had significantly different intakes of macronutrients and CFGHE-defined "other foods." In terms of diet quality determinants, those with poor diet quality had higher frequencies of suboptimal meal behaviours. Students with poor diet quality consumed breakfast and lunch less frequently than did those with average and superior diet quality. CONCLUSIONS: Canadian adolescents have low intakes of CFGHE-recommended foods and high intakes of "other foods." Those with poor diet quality had suboptimal macro-nutrient intakes and increased meal skipping and meal consumption away from home. Adherence to CFGHE may promote optimal dietary intakes and improve nutritional behaviours.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".