Estimating the potential impact on dental caries in children of fluoridating a UK city.
Bibliographic record
Abstract
OBJECTIVE: To estimate the potential reduction in dental caries among 5-6-year-old children in a city in the South West of England after six years of water fluoridation. METHOD: Thirteen out of 35 inner city wards and seven out of 43 outer city wards (sharing the same water supply) having the highest mean dmft of 5-6-year-olds (recorded in a census survey in 2005/6) and/or highest indexes of multiple deprivation (IMD) were the principal focal point. Population demographic data and 5-6-year-old caries prevalence and experience were examined. Mean IMD scores and aggregated, weighted mean values for dmft and caries prevalence were referred to previously published regression analyses of caries levels plotted against IMD for 34 fluoridated (F) and 233 non-fluoridated (NF) health districts in England in order to estimate potential caries reductions. RESULTS: Mean dmft of 5-6-year-olds in the 20 wards with the highest caries levels and/or social deprivation was 2.10 (95% CI 1.87, 2.33) and caries prevalence 49% (95% CI 47%, 52%). In three wards, mean dmft exceeded 2.60. Population of the selected wards was approximately 210,800 with a mean IMD score of 33.70 As a conservative estimate, after six years of fluoridation a caries reduction of > 40% could be expected in 5-6-year-olds for the conurbation overall and for the 20 high caries/high IMD wards, with a gain of 12 percentage points in the absolute proportion caries-free. The overall population of the 78 wards served by the three relevant water treatment works identified was approximately 700,000. CONCLUSIONS: On the basis of current caries levels and population demographics, it appears that a comprehensive fluoridation scheme covering the inner and outer city districts would substantially improve the dental health of the city's children.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".