Fatigue Resistance and Microleakage of CAD/CAM Ceramic and Composite Molar Crowns
Bibliographic record
Abstract
PURPOSE: The aim of this study was to determine effect of compressive cyclic loading on fatigue resistance and microleakage of monolithic CAD/CAM molar ceramic and composite crowns. MATERIALS AND METHODS: Thirty-two extracted molars were prepared to receive CEREC crowns according to manufacturer's guidelines using a special paralleling device (Parallel-A-Prep). Sixteen feldspathic ceramic crowns (VITABLOCS Mark II) (VMII) and 16 resin-composite crowns (Paradigm-MZ100 blocks) (PMZ) were milled using a CEREC-3D machine. Eight crowns of each group were cemented to their respective teeth using self-etching resin cement (Panavia-F-2.0) (PAN), and eight were cemented using self-adhesive resin cement (RelyX-Unicem-Clicker) (RXU). Following storage for 1 week in water, specimens were subjected to uniaxial compressive cyclic loading in an Instron testing machine at 12 Hz for 1,000,000 cycles. Load was applied at the central fossa, and the cycle range was 60-600 N. Specimens were then subjected to microleakage testing. Data were statistically analyzed using factorial ANOVA and Post Hoc (Tukey HSD) tests. RESULTS: All composite crowns survived compressive cyclic loading without fracture, while three ceramic crowns from the subgroup cemented with RXU developed surface cracks at the center of occlusal surfaces, extending laterally. Microleakage scores of ceramic crowns cemented with PAN were significantly lower than those of the other three subgroups (p < 0.05). CONCLUSIONS: After 1,000,000 cycles of compressive cyclic loading, PMZ composite molar crowns were more fatigue-resistant than VMII ceramic crowns. Cement type had a significant effect on fatigue resistance of the ceramic crowns but not the composite ones. Microleakage scores of ceramic crowns cemented with PAN were significantly lower than those of the other subgroups (p < 0.05).
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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) | 0.000 | 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".