<i>University Science Students’</i>: Knowledge of Fats
Bibliographic record
Abstract
PURPOSE: Students entering university often lack knowledge about fats; whether students gain such information during four years at university is unclear. Students' knowledge of fat in the first and fourth years was measured and compared. The effect of a nutrition course on knowledge was also examined. METHODS: A total of 215 science students at a small undergraduate university completed a 15-item, closed-ended questionnaire concerning knowledge of fats in the diet. RESULTS: Fourth-year science students have greater nutrition knowledge of fats than do first-year science students (p<0.005). Given that the majority of first-year students reside on campus and the majority of fourth-year students reside off campus, the purchasing of food and preparation of meals may explain the senior students' greater knowledge of fat. Students who have taken a nutrition course know more about fats than do those who have not (p<0.001). CONCLUSIONS: Taking even one course in nutrition greatly increases nutrition knowledge. Universities could encourage undergraduate students to take a basic nutrition course, which should emphasize the identification and understanding of different types of dietary fats.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".