A Comparison between Atlantic Canadian and National Correction Equations to Improve the Accuracy of Self-Reported Obesity Estimates in Atlantic Canada
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To determine whether obesity correction equations for the Canadian general population, which are dependent on the prevalence of obesity, are appropriate for use in Atlantic Canada, which has the highest obesity rates in the country. Also, to compare the accuracy of the national equations to equations developed specifically for the Atlantic Canadian population. METHODS: The dataset consisted of Canadian Community Health Survey (CCHS) 2007-2008 data collected on 17,126 Atlantic Canadians and a subsample of adults, who provided measured height and weight (MHW) data. Atlantic correction equations were developed in the MHW subsample. Using separate multiple regression models for men and women, self-reported body mass index (BMI) was corrected by multiplying the self-reported estimate by its corresponding model coefficient and adding the model intercept. Paired t-tests were used to determine whether corrected mean BMI values were significantly more accurate (i.e., closer to measured data) than the equivalent means based on self-reported data. The analyses were repeated using the national equations. RESULTS: Both the Atlantic and the national equations yielded corrected obesity estimates that were significantly more accurate than those based on self-report. CONCLUSION: The results provide some evidence of the generalizability of the national equations to atypical regions of Canada.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it