Canadian Community Health Survey 2015: Nutrition Component, Canada Food Guide servings
Bibliographic record
Abstract
The 2015 Canadian Community Health Survey-Nutrition (2015 CCHS-Nutrition) is a nationally-representative survey of the nutrition of people in Canada. The survey provides a rich source of detailed information on food consumption using a 24-hour (hr) dietary recall for the total sample and a repeat sub-sample, nutrient supplement intake, physical measurements, household food insecurity, and other topics that support the interpretation of the 24-hr recall. It also allows the evaluation of changes that have occurred since this survey was last done in 2004. Development and implementation of the 2015 CCHS-Nutrition has been a joint initiative between Health Canada and Statistics Canada, as also occurred for the 2004 CCHS-Nutrition. To facilitate comparison, the 2015 survey used methods that were very similar to the 2004 survey. The over-arching goal of the 2015 CCHS-Nutrition is to provide reliable, timely information about dietary intake, nutritional well-being and their key determinants, with the purpose of informing and guiding programs, policies and activities of federal and provincial governments. The specific objectives of the 2015 CCHS-Nutrition were to: - Collect detailed data on the consumption of foods and dietary supplements among a representative sample of Canadians at national and provincial levels. - Estimate the distribution of usual dietary intake in terms of nutrients from foods, food groups, dietary supplements and eating patterns. - Gather anthropometric (physical) measurements for accurate body weight and height assessment to interpret dietary intake. - Support the interpretation and analysis of dietary intake data by collecting data on selected health conditions and socio-economic and demographic characteristics. - Evaluate changes in dietary intake from the 2004 CCHS-Nutrition.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.019 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".