Tooth–Surface Progression and Reversal Changes in Fluoridated and No–Longer– Fluoridated Communities over a 3–Year Period
Bibliographic record
Abstract
OBJECTIVE: To compare permanent tooth surface-specific progression/reversal changes between fluoridation-ended (F-E) and still-fluoridated (S-F) communities in British Columbia, Canada, over a 3-year period. METHODS: D1D2MFS examinations were contrasted for 2,964 schoolchildren in 1993/94 (grades 2, 3, 8 and 9) and 1996/97 (grades 5, 6, 11 and 12). Generalized Estimating Equation (GEE) models explored the relation between progression/reversal changes and fluoridation status, age, gender, socioeconomic status, and dietary/fluoride histories. RESULTS: Within a scenario of low levels of caries overall, few children had multiple surfaces progressing. At least one smooth surface progressed in 31.4% of subjects; at least one pit-and-fissure (PF) surface progressed in 43.1% of subjects. At least one smooth surface reverted in 89% of subjects who had reversible stages; at least one PF surface reverted in 23.8% of subjects who had reversible stages. GEE (smooth) indicated that odds ratios of progression were twice as large in the F-E site compared to the S-F site, and slightly increased in older participants and in participants exposed to more fluoride technologies. GEE (PF) also indicated that progression was slightly more common in the F-E site; more frequent snacking and lower parental educational attainment had modest associations with increased progression in PF surfaces. For the two types of surfaces, GEE models demonstrated that unerupted surfaces were less likely to progress than sound surfaces. No associations were found between reversals and independent variables. CONCLUSION: Progressions were found to be weakly linked to socio-demographic factors; baseline surface statuses were better predictors of progression. Using the current definitions for disease transitions, F-E communities had more frequent progressions than a S-F community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".