Fluoride Release of Several Types of Fluoride-Containing Restorative Materials According to Fluoride Concentration in Toothpaste
Bibliographic record
Abstract
This study was conducted to investigate the fluoride release of fluoride-containing restorative materials in fluoride recharging according to the concentration of fluoride toothpaste used in Korea. Samples of glass ionomer cement, resin-modified glass ionomer cement, alkasite restorative material, and composite resin were prepared and fluoride release was measured on days 1, 3, 7, 14, 21, 28. Thereafter, fluoride-free, 500 ppm, and 1450 ppm fluoride toothpaste was applied to each restorative materials, and the fluoride release was measured on days 1, 3, 7. Glass ionomer cement showed the highest cumulative fluoride release until the 7th day of measurement, and from the 14th day onwards, the resin-modified glass ionomer cement showed the highest cumulative fluoride release, but there was no significant difference. When restorative material groups were recharged with 500 ppm of fluoride toothpaste, the fluoride release was significantly higher only for the alkasite restorative material compared to the fluoride-free toothpaste group (p < 0.017). When restorative material groups were recharged with 1450 ppm of fluoride toothpaste, the fluoride release was significantly higher in all restorative groups compared to the fluoride-free toothpaste group (p < 0.017).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".