A Comparison Study of the Osseointegration of Zirconia and Titanium Dental Implants. A Biomechanical Evaluation in the Maxilla of Pigs
Bibliographic record
Abstract
OBJECTIVES: The purpose of the present study was to investigate the osseointegration of microstructured zirconia implants in comparison with sandblasted and acid-etched (SLA) titanium implants in a biomechanical study. MATERIALS: Zirconia implants (4.1 mm in diameter, 10 mm in length) were produced using a new low pressure injection molding technique. After that the implants were acid-etched with hydrofluoric acid. Standard Ti-SLA implants of the exact same shape served as controls. Six months after extraction of incisors 2 and 3, 16 adult pigs received a total of 64 implants in the maxillae. After 4, 8, and 12 weeks the animals were sacrificed, and 59 implants could be analyzed to removal torque (RTQ) testing. RESULTS: The mean RTQ values for zirconia implants were 42.4 Ncm at 4 weeks, 69.6 Ncm at 8 weeks, and 69.3 Ncm at 12 weeks of healing, whereas RTQ values for the Ti-SLA implants were 42.1 Ncm, 75.0 Ncm, and 73.1 Ncm at corresponding time intervals. There is no statistical difference in RTQ values between Ti-SLA and zirconia implants at 8 weeks. CONCLUSIONS: Within the limits of the present study it was concluded that acid-etching of zirconia implants enhances bone apposition resulting in RTQ values which were equivalent to that of Ti-SLA.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".