Clinical performance of chairside monolithic lithium disilicate glass‐ceramic CAD‐CAM crowns
Bibliographic record
Abstract
OBJECTIVES: To evaluate the clinical performance and the effect of various patient and provider-related factors on the longevity of chairside monolithic posterior lithium disilicate glass-ceramic (LDGC) computer-aided design (CAD)-computer-aided manufacturing (CAM) crowns provided by predoctoral students. MATERIALS AND METHODS: A sample of posterior LDGC CAD-CAM crowns was evaluated. Crown preparations were milled chairside using the CEREC Omnicam system and cemented with Rely-X Unicem or Calibra Universal resin cements. Clinical assessment of the crowns and supporting periodontal structures was performed using the modified California Dental Association (CDA) criteria. Intraoral photographs as well as radiographs were taken for further assessment by two evaluators. Kaplan-Meier survival analysis was performed. RESULTS: A total of 40 crowns were inserted in 32 patients and evaluated for 4 years. Three complications were observed (two-technical and one-biological). No chipping or fracture of crowns was observed. No significant association was found between age, sex, periodontal condition, tooth type, tooth vitality, cement type, and longevity. The 4-year cumulative survival and success rates were 95.0 and 92.3%, respectively. CONCLUSION: Chairside LDGC CAD-CAM crowns exhibited a high survival rate after 4 years in function and were shown to be a viable and reliable treatment option for posterior teeth. CLINICAL SIGNIFICANCE: The high survival rate of chairside CAD-CAM crowns observed in this study suggests the likelihood of predictable performance in the predoctoral setup.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".