Fruit and vegetable intake of students and prevalence of vegetarianism at Lakehead University / by Hesam Kooshesh.
Bibliographic record
Abstract
Purpose : The purpose of this study was to assess the daily intake levels of fruits and vegetables in a population of post-secondary students at Lakehead University in Thunder Bay, Ontario [Northwestern Ontario] and to measure the prevalence rate of vegetarianism in this population. \nMethods: Food intake, demographic variables and vegetarian status were measured with a survey and food frequency questionnaire (FFQ) filled out by students who ate at the Aramark residence cafeteria of Lakehead University between Sunday February 1st and Saturday February \n7th, 2009. Two hundred sixty-seven students participated, of which 197 were on the Aramark meal plan and therefore ate all of their meals at this cafeteria (response rate= 43.5% for this group). \nResults: Forty-three percent of the sample was female, with a mean age of 21 ? 3 years of age. Mean intake of fruits and vegetables was 5.0 ? 2.3 servings/day for females and 4.6 ?2.1 servings/day for males. Females ate significantly more vegetables than males (p < 0.01), Caucasians ate more fruits and vegetables than non-Caucasians (p < 0.01) and vegetarians ate \nmore fruits and vegetables than non-vegetarians (p < 0.01). Within the sample, 6.7% (18/267) self-reported as vegetarian, with the majority being female (14/18) and ovo-lacto vegetarian (13/18). \n Conclusions : Fruit and vegetable intake in this population is below recommended levels and below the estimated national average for their age group. Males, non-vegetarians and non-Caucasians are at a particular risk of future health deficits due to insufficient fruit and vegetable intake. The prevalence of vegetarianism among Canadian post-secondary students may be higher than in the rest of Canada.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".