A cross-sectional analysis of student fruit and vegetable consumption at the University of Ontario Institute of Technology
Bibliographic record
Abstract
Access to nutritious food is imperative for maintaining overall health. Fruits and vegetables are foods that are nutrient rich, and consumption of these foods is related to positive health outcomes. The purpose of this study was to determine fruit and vegetable consumption for students in the Faculty of Health Sciences at the University of Ontario Institute of Technology and what food retailers they frequent. The study found that students reported a daily fruit and vegetable consumption lower than the minimum daily amount recommended by Canada???s Food Guide. Students were also shown to frequent sit-down food retailers that offered diverse dietary options (low-sodium, gluten-free, and vegetarian). There was an association between students who visited stores that offered fewer options and increased consumption of potatoes. Low consumption of fruit and vegetables can lead to health complications, such as increased risk for cardiovascular disease and cancer, and should be addressed to reduce risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".