Community Water Fluoridation in Canada - Trends, Benefits, and Risks
Bibliographic record
Abstract
• Fluoride has been added to public drinking water in Canadian communities since the 1940s as a means of preventing tooth decay. • Dental fluorosis is a known adverse effect of excessive fluoride exposure during tooth formation. Fluorosis ranges from barely noticeable whitish striations in the enamel to severe pitting and brownish staining. In general, the prevalence of dental fluorosis in communities with water fluoridation is higher in comparison to non-water fluoridated communities. • No evidence was found for an association between water fluoridation and any of the following adverse outcomes: bone mineral density, bone fractures, bone cancer, or cancer in other body tissues. • The best available evidence supports the finding that water fluoridation reduces the prevalence of dental caries, although this benefit of fluoridation may be limited due to multiple sources of exposures to fluoride that are now available to the public.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".