Marginal fit and internal adaptation of monolithic zirconia 3-unit fixed dental prostheses : in-vitro study
Bibliographic record
Abstract
Objectives: To compare marginal fit and internal adaptation of monolithic zirconia (MZ) 3-unit fixed dental prostheses (FDPs) fabricated using two workflows: a full-chairside computer aided design/computer aided manufacturing (CAD/CAM) one (FCH) and a lab CAD/CAM one (LAB). Methods: Teeth #14 and #16 were prepared for MZ 3-unit FDP on an ivorine typodont. A total of 30 MZ 3-unit FDPs was fabricated using two processes: FCH and LAB. A CEREC Primescan intraoral scanner was used in both workflows to digitize the typodont model. FCH FDPs (n=15) were designed using CEREC SW 4.5.1 and milled using CEREC MC X. LAB FDPs (n=15) were designed using Exocad and milled using Zirkonzhan 600/V3 milling chamber. A fast-sintering protocol was used in both groups. A dual-scan technique was utilized to assess the cement space. The fit was evaluated at systematically selected areas: occlusal surface (OC), axial wall (AX) and margin (MA). Statistical analysis of the results was performed using univariate analysis of variance (ANOVA) with Scheffè post hoc test (P=0.05). Results: The measurements in FCH and LAB groups are within the clinically acceptable marginal and internal fit. The MA, AX and OC fit at retainer 14 of the FCH FDPs is 87.60 ±30. µm, 104.80 ±25.84 μm and 158.53 ±25.08 μm respectively, and of the LAB FDPs is 105 ±23.19 μm, 117.60 ±20.48 μm and 146.53 ±19.27 μm respectively. The MA, AX and OC fit at retainer 16 of the FCH FDPs is 67.40 ±26.50 μm, 94.53 ±15.51 μm and 141.53 ±34.34 μm respectively, and of the LAB FDPs is 95.53 ±30.51 μm, 115.47 ±15.66 μm and 138.07 ±20.36 μm respectively. The difference between the two groups is not statistically significant. Conclusion: The MZ 3-unit FDPs fabricated using FCH have clinically acceptable marginal and internal fit. This verifies the efficiency of FCH workflow in fabricating MZ multi-unit FDPs in a single visit, especially useful for people who cannot attend multiple visits to receive the restoration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".