Junk Food and Micronutrient Intakes among Undergraduate Students in Ontario, Canada
Bibliographic record
Abstract
Canadian Dietary Guidelines recommend limiting unhealthy foods but provide no cut-offs for acceptable intakes. One possible consequence of excess junk food intake is nutrient dilution. The objective of this study was to determine the relationship between junk food and micronutrient intakes. Data were obtained through a cross-sectional study of 199 University of Guelph students. Micronutrient intakes were assessed by tertiles of junk food consumption. Total junk foods constituted 20% and 25% of daily kilocalories among male and female participants, respectfully. Micronutrient intakes were similar across tertiles of junk food intake. Participants in the highest tertile of high salt, high fat food intake had significantly higher intakes of sodium. This study shows that, in this population of university students, junk food intakes do not significantly contribute to micronutrient dilution. It may be warranted to limit intakes of junk food based on other dietary components, such as sodium, saturated fat, and/or sugar
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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 | 0.001 | 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".