Bibliographic record
Abstract
OBJECTIVES: This report is an overview of Canadians' eating habits: total calories consumed and the number of servings from the various food groups, as well as the percentage of total calories from fat, protein and carbohydrates. DATA SOURCES: The data are from the 2004 Canadian Community Health Survey (CCHS) - Nutrition. Published results from the 1970-1972 Nutrition Canada Survey were used for comparisons over time. ANALYTICAL TECHNIQUES: An initial 24-hour dietary recall was completed by 35,107 people. Asubsample of 10,786 completed a second recall 3 to 10 days later. Data collected in the first interview day were used to estimate, by selected characteristics, average calorie intake and average percentages of calories from fat, protein and carbohydrates. Usual intake of macronutrients was estimated with the Software for Intake Distribution Estimation (SIDE) program, using data from both interview days. MAIN RESULTS: Although a minimum of five daily servings of vegetables and fruit is recommended, 7 out of 10 children aged 4 to 8 and half of adults did not meet this minimum in 2004. More than a third of 4- to 9-year-olds did not have the recommended two daily servings of milk products. Over a quarter of Canadians aged 31 to 50 obtained more than 35% of their total calories from fat. Snacks account for more calories than breakfast, and about the same number of calories as lunch.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| 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) | 0.019 | 0.002 |
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".