Different Strategies to Bond Bis-GMA-based Resin Cement to Zirconia.
Bibliographic record
Abstract
PURPOSE: To evaluate the effect of different bonding strategies on short- and long-term bis-GMA-based resin cement bond strengths to zirconia. MATERIALS AND METHODS: One hundred twenty samples of fully-sintered zirconia (Prettau Zirconia) were sandblasted and randomly distributed into 5 groups (n = 24): UA: Scotchbond Universal Adhesive; SZP: Signum Zirconia Bond I + II; ZPP: Z-Prime Plus; EXP: MZ experimental primer; CO: no primer application (control). After performing these surface treatments, translucent tubes (0.8 mm diameter and 1.0 mm height) were placed on the zirconia specimens, and bis-GMA-based cement (Duo-Link) was injected into them and light cured. Specimens were tested for microshear bond strength either 24 h or 6 months (m) after water storage (37°C) and surfaces were characterized by SEM and EDX. Two-way ANOVA and Tukey's post-hoc test (p < 0.05) were used to evaluate bond strength results. RESULTS: The mean bond strengths (MPa ± SD) were: UA=14.6 ± 4.7a (24 h); 16.0 ± 4.8a (6 m); SZP = 14.0 ± 5.4ab (24 h); 11.9 ± 2.6ab (6 m); ZPP=8.0 ± 1.8b (24 h); 8.6 ± 3.3b (6 m); EXP = 1.2 ± 0.5c (24 h); 0.6 ± 0.7c (6 m); CO=1.0 ± 1.2c (24 h); 1.3 ± 1.2c (6 m). Bonding strategy significantly influenced bond strength (p = 0.0001), but storage time did not (p = 0.841). Groups UA and SZP showed a homogeneous layer covering the zirconia surface. In these groups, EDX demonstrated the presence of phosphorus. Group ZPP resulted in a nonhomogeneous layer, exposing the zirconia substrate underneath. EXP application resulted in an undetectable layer. CONCLUSION: Water storage did not affect resin cement bond strengths to zirconia irrespective of the surface treatment. Bis-GMA-based resin cement bond strengths to zirconia are affected by specific bonding strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".