Flexural Properties of Chairside CAD/CAM Materials
Bibliographic record
Abstract
Background. New blocks for milling crowns using CAD-CAM technology were introduced to the profession. It is important to determine mechanical properties of such materials since they are used for the fabrication of crowns used in stress-bearing areas.Objectives. This study determined the flexural strength (FS) and the flexural modulus (FM) of 2 glass-ceramic and 2 nanoceramic resin composite CAD/CAM blocks used for chair-side crown fabricationMaterial and Methods. Rectangular specimens were cut from 4 different CAD-CAM blocks. Specimens were 3 mm wide, 1.2 mm thick 14 mm long. Specimens were subjected to 3-point bending test following ISO guidelines (ISO 6872) at cross-head speed of 0.5mm/min. The flexural strength (FS) and the flexural modulus (FM) were calculated and the data statistically-analyzed with one-way ANOVA and Games Howell multiple comparison tests at 95% confidence interval.Results. Means and SDs of FS (MPa) for VE, LU, E-max, E-max-U, CD, CD-U were: 123.97(14.84), 168.07(16.70), 334.10(54.3), 128.90(17.6), 177.32(37.54) and 147.61(26.62) respectively. For FM means and SDs were: 17.18(2.03), 9.75(0.51), 44.8(5.52), 35.14(7.46), 32.96(6.55) and 38.90(8.03) for VE, LU, E-max, E-max-U, CD, CD-U, respectively. ANOVA revealed a highly significant difference among group means (p < 0.0001) for both FS and FM. E-max had significantly highest mean FS and FM values among all groups, while VE showed lowest FS and LU lowest FM means. Firing and or crystallization positively affected both flexural properties of E-max, but only FS of CD.Conclusion. A wide variability in mean FS and FM was observed among the tested materials. Generally, glassceramic based materials had superior flexural properties.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.010 | 0.002 |
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".