Favorable residual stress induction by resin-cementation on dental porcelain
Bibliographic record
Abstract
Despite developments in polycrystalline ceramics, glassy dental-ceramic materials provide the optimum cosmetic option in most clinical situations to mimic the natural dentition. The clinical success of glassy dental-ceramic materials is often attributed to resin-adhesive bonding techniques. In this study we explore whether shrinkage stresses generated on photo-polymerisation of the resin-cement are sufficient to induce ceramic surface defect stabilization, and we quantify the transient nature of the induced stresses. Stress-induced changes in a feldspathic ceramic over a range of thicknesses (0.5–2.0 mm: n = 20 per thickness) were measured using a profilometric technique at baseline for each disc-shaped specimen (mean of the maximum deflection (δbaseline)) and again following polymerisation of a controlled resin-cement thickness on the contra-lateral surface. Measurements were repeated at 30, 60, 90 and 1440 min following photo-polymerization (δ30, δ60, δ90 and δ1440, respectively) before bi-axial flexure strength (BFS) determination at 24 h. A repeated measures ANOVA and post-hoc Bonferroni tests determined that δ1440 was significantly different from δbaseline (p = 0.02), δ30 (p < 0.01) and δ60 (p < 0.01) but not δ90 (p = 0.61). Data exploration revealed that there were differences in directionality of the independent variable (mean of the maximum deflection (δ)) with a proportion of specimens increasing in deflection and others reducing. The directionality of the effect strongly correlated with the BFS values. Where δ1440-δbaseline was low and/or negative, BFS values were also low. High BFS values were observed when δ1440-δbaseline was large and positive (indirectly inferring high shrinkage-stress-induced-deformation). A link between shrinkage stresses associated with the photo-polymerization of dental resin-based cements and the reinforcement of dental porcelain has clearly been established.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".