Comparative analysis of zirconia and lithium disilicate all-ceramic crowns manufactured using digital versus digital-conventional technique
Bibliographic record
Abstract
Case presentation: This study aimed at presenting and evaluating two manufacturing technologies and two types of restorative materials (3rd generation zirconia oxide and lithium disilicate glass ceramic) for the rehabilitation of the upper anterior teeth. The outcomes were evaluated in terms of aesthetics, marginal adaptation, technologies and materials used, working protocol, time and costs. Materials and method: A model with ideal preparations for the six upper anteriors was used in order to manufacture three zirconia oxide single units (Zirtooth Multi A2, Hass Corp) using the full digital protocol (1st hemiarch) and three lithium disilicate single units (Amber Press, LT, A2, Hass Corp) using the combined digital-analog protocol (2nd hemiarch). After fabrication, final layers of stains and glaze were applied for a better individualisation of the final restorations. The six restorations were evaluated on a printed model in order to asses the marginal fit, the final aesthetics, the optical characteristics and the elements of macro and microtexture. Discussions/Conclusions: The two materials used together with the two different manufacturing techniques have produced very similar results, in accordance with the naturalness of teeth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".