Survival and Chipping of Zirconia‐Based and Metal–Ceramic Implant‐Supported Single Crowns
Bibliographic record
Abstract
PURPOSE: The objective of this retrospective study was to compare the incidence of chipping of implant-supported, all-ceramic, and metal-ceramic single crowns. MATERIAL AND METHODS: One hundred fifty-three patients (51.7% male, mean age 55.0 years) received 232 cemented implant-supported single crowns. One hundred and seventy-nine crowns had a metal framework (gold alloy) and 53 crowns were all-ceramic (zirconia framework and glass-ceramic veneer material). Age, gender, kind of cementation, and location of the restorations were assessed as possible factors affecting chipping. RESULTS: During the observation period of up to 5.8 years (mean 2.1 years; standard deviation 1.4), a total of 13 (24.5%) all-ceramic and 17 (9.5%) metal-ceramic crowns suffered from chipping, a difference that was statistically significant. A total of ten single crowns had to be remade resulting in survival of 86.8% (all-ceramic) and 98.3% (metal-ceramic). The other possible factors did not have a significant effect on the chipping. CONCLUSION: Chipping was found to be more frequent for all-ceramic implant-supported single crowns. If the reasons for the vulnerability of all-ceramic crowns remain unknown, implants with all-ceramic single crowns should generally be recommended with care.
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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 | 0.004 |
| 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 | 0.000 | 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".