Bibliographic record
Abstract
BACKGROUND: CAD/CAM technology in combination with zirconia ceramic has increasingly gained popularity in implant dentistry. PURPOSE: This narrative review presents the current knowledge on zirconia utilized as framework material for implant-borne restorations and implant abutments, laboratory tests and developments, clinical performance, and possible future trends for implant dentistry are addressed. MATERIAL AND METHODS: A review of available literature from 1990 through 2010 was conducted with search terms zirconia,""implants,""abutment,""crown," and "fixed dental prosthesis" using electronic databases (PubMed) and manual searching. RESULTS: Latest applications of zirconia in implant dentistry include implant abutments, multiple unit and full-arch frameworks as well as custom-made bars to support fixed and removable prostheses. High biocompatibility, low bacterial surface adhesion as well as favorable chemical properties of zirconia ceramics are reported. Zirconia stabilized with yttrium oxide exhibits high flexural strength and fracture toughness due to a transformation toughening mechanism. Preliminary clinical data confirmed the high stability of zirconia for abutments and as a framework material for implant borne crowns and fixed dental prostheses. Zirconia abutment or framework damage has rarely been encountered. However, veneering porcelain fractures are the most common technical complication in implant-supported zirconia restorations. These porcelain veneer failures have led to concerns regarding differences in coefficient of thermal expansions between core and veneering porcelain and their respective processing techniques. CONCLUSION: As presently evidence of clinical long-term data is missing, caution with regard to especially extensive implant-borne zirconia frameworks is recommended.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".