Digital microscopic evaluation of vertical marginal discrepancies of CAD/CAM fabricated zirconia cores
Bibliographic record
Abstract
OBJECTIVE: The aim of this in vitro research study was to evaluate the vertical marginal discrepancies of zirconia (Zr) cores fabricated by five different computer-aided design and manufacturing (CAD/CAM) systems using a digital microscope. MATERIALS AND METHODS: A total of 60 specimens were prepared and randomly divided into five groups (n=12 each) using the following systems: Ceramill Motion 2 (CM, Amanngirrbach, Germany); Weiland (WI, Ivoclar Vivadent, USA); Cerec (CS, Sirona Dental, USA); Zirkonzahn (ZZ, Gmbh Bruneck, Italy) and Cad4dent (CD, Canada). The specimens were numbered and the vertical marginal discrepancies were evaluated with a digital microscope at 50× magnification. RESULTS: A one-way analysis of variance showed a statistically significant difference (p=0.002) between the groups. The CM group exhibited the lowest values for the marginal gaps (31.30±15.12 μm), while the ZZ group exhibited the highest values for the marginal gaps (44.83±28.76 μm) compared to other groups. A post hoc Tukey's test for multiple comparisons between the experimental groups showed a statistically significant difference (p<0.05) between the group CM and group CD with group ZZ. The rest of the groups showed no significant differences between them. Variations in the values were observed for the four sites measured with the highest and the least mean marginal gap value of 43.19±23.84 μm and 32.49±12.21 μm for buccal and lingual sites, respectively. CONCLUSION: Variations existed in the marginal discrepancy values for the CAD/CAM systems investigated in the study. Vertical marginal discrepancy values observed for various systems investigated in the study were well within the clinically acceptable range.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".