Advancements in all-ceramics for dental restorations and their effect on the wear of opposing dentition
Bibliographic record
Abstract
ABSTRACT Tooth wear is a process that is usually a result of tooth to tooth and/or tooth and restoration contact. The process of wear essentially becomes accelerated by the introduction of restorations inside the oral cavity, especially in case of opposing ceramic restorations. The newest materials have vastly contributed toward the interest in esthetic dental restorations and have been extensively studied in laboratories. However, despite the recent technological advancements, there has not been a valid in vivo method of evaluation involving clinical wear caused due to ceramics upon restored teeth and natural dentition. The aim of this paper is to review the latest advancements in all-ceramic materials, and their effect on the wear of opposing dentition. The descriptive review has been written after a thorough MEDLINE/PubMed search by the authors. It is imperative that clinicians are aware of recent advancements and that they should always consider the type of ceramic restorative materials used to maintain a stable occlusal relation. The ceramic restorations should be adequately finished and polished after the chair-side adjustment process of occlusal surfaces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".