Success of Veneers with Indirect Resin Composite
Bibliographic record
Abstract
Objective: To evaluate the success of veneers fabricated with indirect resin composite (Ceramage). Method: This Descriptive Case Series was completed at de’ Montmorency college of dentistry/Punjab Dental Hospital, Lahore over the period of 6 months from Jul 2018 to Jan 2019. Patients fulfilling the inclusion criteria of the study were selected. After the informed consent, pre-operative radiographs of the teeth to be veneered were taken to rule out any caries activity or periapical pathology. A total of 60 veneers were fabricated with indirect resin composite. Patients were followed up with 6 months interval and restorations were evaluated for complications like dislodgment, chipping, fracture, sensitivity and bleeding from gums. Results: Out of total of 60 veneers 50 were successful and 10 were unsuccessful. only 4 showed slight postoperative sensitivity,4 showed moderate postoperative sensitivity and 2 showed severe postoperative sensitivity.out of total 5 showed minor crack lines,3 showed minor chipping (1/4 of the restoration) and 2 showed moderate chipping (1/2 of restoration). Success rate of veneers fabricated with indirect resin composite (Ceramage) was 83.3%. Conclusions: The indirect veneers have undergone considerable improvement and refinement over the past few decades and have now matured into a predictable restorative concept in terms of longevity, periodontal response and patient satisfaction. The design of the restoration should take the material properties into account in order to enhance the clinical performance. Key words: Indirect Resin Composite, Veneers, Smile makeover
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".