Topography, Microhardness, and Precision of Fit on Ready‐Made Zirconia Abutment Before/After Sintering Process
Bibliographic record
Abstract
BACKGROUND: Sintering porcelain on a ceramic abutment may change the microstructure and result in aging processes that influence the mechanical properties, internal strain, and the three-dimensional form of the abutment, thus causing a possible misfit between the abutment and the fixture. PURPOSE: The aim was to investigate topography, microhardness, and precision of fit on yttrium-stabilized zirconia (Y-TZP) abutments before/after the sintering process. MATERIALS AND METHODS: Ten Y-TZP abutment samples were ground to a shape used in the clinical situation and divided at random into two groups: before/after sintering. After the surface roughness was measured on all abutments, the abutments were connected to fixture replicas, embedded in resin, and cut in the longitudinal axis. Both sides of the cut samples were measured with respect to microhardness and minimum distance between fixture and abutment surface. t-Test, one-way analysis of variance, and Bonferroni multiple comparisons were used to investigate statistical significant differences. RESULTS: The surface roughness (S(a) and S(dr)) after sintering was significantly higher than before sintering. The total average values of microhardness after sintering were statistically lower than before sintering with a difference of 2%. The total distance between abutment/fixture before/after sintering demonstrated no statistically significant difference. Contact between abutment/fixture was most common at the top area of the fixture. CONCLUSION: A slight decrease of microhardness and contamination of porcelain particles immediately below the veneered part were found on the Y-TZP abutment after sintering. The sintering process did not affect the precision of fit.
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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) | 0.000 | 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".