In Vitro Wear Behavior of Zirconia Opposing Enamel: A Systematic Review
Bibliographic record
Abstract
PURPOSE: The aim of this systematic review was to assess enamel wear on teeth opposing zirconia restorations and to evaluate factors related to the wear of natural teeth opposing zirconia restorations. MATERIALS AND METHODS: Five electronic databases were searched through May 2013 without limitations. The terms "antagonist*," "enamel," "wear," and "zirconi*" were used. Titles and abstracts were initially screened, and those that fulfilled the inclusion criteria were selected for a full-text assessment. Studies that evaluated only the material wear were not included. RESULTS: The database search strategy retrieved 142 potentially eligible studies. After the duplicate studies were removed, 62 studies were obtained. Titles and abstracts that fulfilled the inclusion criteria were selected for a full-text assessment (25). Seven laboratory studies met the inclusion criteria. In addition, reference lists from the finally selected studies were also screened. CONCLUSIONS: There was a large variation in relation to wear test method quantification, applied force, lateral movement, number and frequency of cycles, number of specimens, and enamel specimen preparation. In all studies, enamel wear rates were lower against polished zirconia. Differences in the test methods did not allow for comparisons of wear rates among the studies. CLINICAL SIGNIFICANCE: Polishing the surface is recommended for a full-contour zirconia restoration because polished zirconia presents favorable wear behavior opposing natural teeth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".