Evaluation of the Mechanical and Adhesion Characteristics of Indirect Restorations Manufactured with Three-Dimensional Printing
Bibliographic record
Abstract
The aim of this study was to investigate the marginal fit and bond strength characteristics of onlay restorations manufactured by three-dimensional printing (Varseo XS, Bego GmbH, Bremen, Germany) and CAD/CAM (CAMcube, Montreal, QC, Canada) systems. Class II onlay cavities on sixty mandibular molars were prepared in cavities and restored in three separate groups using different fabrication methods. Digital and conventional impressions were taken to design the restorations in the CAD system (DWOS, Straumann GmbH, Freiburg, Germany). To evaluate the marginal fit and void volumes, all specimens were scanned with microcomputed tomography. A microshear test was performed to compare the bond strength of the restorations to the tooth surface. The marginal fit values measured for the 3D-printed and CAD/CAM onlay restorations were found to be at clinically acceptable levels (<120 µm), and no significant difference could be observed between the three different fabrication methods (p > 0.05). According to the microshear test results, the CAD/CAM group had the highest bond strength values before (34.82 MPa) and after (26.87 MPa) thermal cycling (p < 0.05), while the 3D-printed and conventionally produced onlays had similar results (p < 0.05). 3D printing technology is a promising option for indirect restorations; however, the post-production phase is as crucial as the printing and cementation phases.
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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 | 0.000 | 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".