Influence of curing protocol and ceramic composition on the degree of conversion of resin cement
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Due to increasing of aesthetic demand, ceramic crowns are widely used in different situations. However, to obtain long-term prognosis of restorations, a good conversion of resin cement is necessary. To evaluate the degree of conversion (DC) of one light-cure and two dual-cure resin cements under a simulated clinical cementation of ceramic crowns. MATERIAL AND METHODS: Prepared teeth were randomly split according to the ceramic's material, resin cement and curing protocol. The crowns were cemented as per manufacturer's directions and photoactivated either from occlusal suface only for 60 s; or from the buccal, occlusal and lingual surfaces, with an exposure time of 20 s on each aspect. After cementation, the specimens were stored in deionized water at 37°C for 7 days. Specimens were transversally sectioned from occlusal to cervical surfaces and the DC was determined along the cement line with three measurements taken and averaged from the buccal, lingual and approximal aspects using micro-Raman spectroscopy (Alpha 300R/WITec®). Data were analyzed by 3-way ANOVA and Tukey test at =5%. RESULTS: Statistical analysis showed significant differences among cements, curing protocols and ceramic type (p<0.001). The curing protocol 3x20 resulted in higher DC for all tested conditions; lower DC was observed for Zr ceramic crowns; Duolink resin cement culminated in higher DC regardless ceramic composition and curing protocol. CONCLUSION: The DC of resin cement layers was dependent on the curing protocol and type of ceramic.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it