Under-reporting of energy intake in the Canadian Community Health Survey.
Bibliographic record
Abstract
BACKGROUND: Under-reporting of food consumption is a recurrent challenge for nutrition surveys. Past research suggests that under-reporting tends to be most pronounced among overweight and obese people. DATA AND METHODS: Data from 16,190 respondents to the 2004 Canadian Community Health Survey (CCHS 2.2)-Nutrition were used to estimate underreporting of food intake for the population aged 12 or older in the 10 provinces. Multiple linear regression models were used to assess the impact of different characteristics on underreporting. RESULTS: Average under-reporting of energy intake was estimated at 10%. Under-reporting was greater among people who were overweight or obese, those who were physically active, adults compared with teenagers, and women compared with men. INTERPRETATION: Under-reporting of energy intake is not random and varies by key health determinants. Awareness of the characteristics associated with under-reporting is important for users of nutrition data from the CCHS 2.2.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".