<i>Primary Food Sources of Nutrients</i>In the Diet of Canadian Adults
Bibliographic record
Abstract
PURPOSE: Food sources of nutrients in the Canadian diet were explored. Knowledge of these sources is important to public health professionals and to those in clinical practice. METHODS: Using data from the Food Habits of Canadians study, we investigated nutrient sources from detailed food groupings in a sample of 1,543 adults (971 women, 572 men) from across Canada. Subjects were interviewed by trained dietitians. At the time of the interview, a sociodemographic questionnaire and a 24-hour dietary recall were completed. RESULTS: The response rate was 30%. Subjects aged 18 to 34 reported eating more prepared and convenience foods than did those aged 35 to 65. Energy was contributed mainly by breads, pasta, rice, grains, and fluid milk. Protein intake was primarily derived from meat and dairy products; legumes, nuts, seeds, and eggs were not high contributors. For men aged 35 to 65 and women aged 18 to 65, butter, margarine, and oil were the primary fat sources; they were the second most common source for men aged 18 to 34. Fibre was provided by foods that are not usually considered good sources, but because of the large total consumption of these foods, they are important in Canadians' diet. The main source of calcium was dairy products, and iron came mainly from non-heme sources. CONCLUSIONS: We must understand the contributions of foods to nutrients, and distinguish "important" sources of nutrients (those consumed by many in substantial amounts) from "good" sources (foods rich in particular nutrients, whether eaten or not).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".