Success rate of prepared and unprepared sealants in children with low and moderate-high caries risk
Bibliographic record
Abstract
This retrospective study’s aim was to examine the success rate of prepared and unprepared sealants at different ages of placement, and to determine if caries risk played a role in the sealants’ success. Data was collected from 1,173 first molars subjects from a private pediatric dental clinic (Children’s Dental World, Winnipeg, Manitoba). These were categorized based on initial treatment types (unprepared sealants (55%), prepared sealants (38%), and non-treated (7%)), and then further analyzed by their initial caries risk (low (27%) or moderate-high (73%)). Treatment failure and success were assessed at 12-months and 24-months post-treatment. Overall, in a 24-month period, both sealant methods were found to be highly successful with an overall average of 97% at 12-months and 93% at 24-months. The prepared sealants method statistically did not have significantly more failures (3.24% and 4.31%) than unprepared sealants (3.67% and 2.71%) at both recall periods. There were more failures for the sealants when placed at age 5, 6, and 7 years (5.54% and 5.88%) at 12-months and 24-months. Initial and change in caries risk status did not seem to have an impact on the overall success rate of sealants. The highest success rate for sealed molars was found when subjects consistently remained at low caries risk over the 24-month period (Group 1 97.60%) but it was found to be statistically insignificant. Overall, both sealant methods are highly successful in preventing occlusal caries on first permanent molars, regardless of caries risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".