FLUORIDATION EXPOSURE STATUS BASED ON LOCATION OF DATA COLLECTION IN THE CANADIAN HEALTH MEASURES SURVEY: IS IT VALID?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Statistics Canada's population health surveys may be an important source of up-to-date evidence on fluoridation and population oral health. The objective of this study was to examine the validity of a geographic measure of fluoridation from a national survey (based on site of data collection), by comparing it with estimates of fluoride level from urine samples. METHODS: The data source is the environmental urine subsample (n=2563) from Cycle 2 (2009-2011) of the Canadian Health Measures Survey. Mean comparison and multivariable linear regression were used to examine whether urinary fluoride levels differed between respondents classified as "fluoridated" versus "non-fluoridated" based on data collection site. RESULTS: Respondents who attended data collection sites classified as fluoridated had significantly higher mean urinary fluoride levels than those who attended sites classified as non-fluoridated. This effect was robust to adjustment for covariates and was somewhat stronger among an "exposed" subpopulation (defined based on tap water consumption and residential history) compared with a non-exposed subpopulation. No apparent added value was associated with using a more precise geographic indicator based on home postal code. CONCLUSIONS: Fluoridation status based on data collection site seems crude, but is actually reasonably accurate compared with fluoride level in urine, in the context of a large national Canadian survey of urban and rural residents. Although findings are of limited use for individual-level risk assessment, they may be of interest to dental public health researchers and to those engaged in public health surveillance, because they inform efficient and readily available options for monitoring fluoridation status in populations.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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