Assessment of the Internal Fit of Lithium Disilicate Crowns Using Micro‐CT
Bibliographic record
Abstract
PURPOSE: The aim of this study was to compare the internal fit of lithium disilicate crowns fabricated using digital technology with those fabricated by conventional means. MATERIALS AND METHODS: Forty-five lithium disilicate crowns were fabricated: 15 using digital impression and computer-aided design/computer-aided machining technique (group 1), 15 from the same digital impressions, but using a conventional die and laboratory fabrication process (group 2), and 15 using a conventional poly (vinyl siloxane) (PVS) impression and laboratory fabrication process (group 3). Tooth #15 was prepared for all-ceramic restoration on an ivorine typodont, which was digitized and a replica milled in zirconia to serve as master model. The master zirconia model was used for the impression procedures. Duplicate dies of the master zirconia die were made in polyurethane, enabling the internal fit of each crown to be evaluated using X-ray microcomputed tomography. The total volume of the internal space between the crown and die, the mean and maximum thickness of this space, and the percentage of the space that was at or below 120 μm thickness was calculated for each group and statistically tested for significant difference using one-way ANOVA, with post hoc Scheffé analysis. RESULTS: Group 1 crowns resulted in a smaller volume of internal space (12.49 ± 1.50 mm(3)) compared to group 2 (15.40 ± 2.59 mm(3) ) and to those of group 3 (18.01 ± 2.44 mm(3)). The mean thickness of the internal space for group 1 (0.16 ± 0.01 mm) and for group 2 (0.17 ± 0.03 mm) was significantly lower than that of group 3 (0.21 ± 0.03 mm). The average percentage of the internal space of a thickness of 120 μm and below was different between the three groups: 46.73 ± 5.66% for group 1, 37.08 ± 17.69% for group 2, and 22.89 ± 9.72% for group 3. Three-dimensional renderings of the internal space were also created. CONCLUSIONS: The results of this study suggested that pressed and milled IPS e. max crowns from LAVA COS digital impressions had a better internal fit to the prepared tooth than pressed IPS e.max crowns from PVS impressions in terms of total volume of internal space, average thickness of internal space, and percentage of internal space at or below 120 μm.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".