Maxillary Sinus Augmentation with a New Xenograft: A Randomized Controlled Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Insufficient residual alveolar bone height is a common deterrent in the placement of dental implants in the posterior maxilla. The use of autografts, xenografts, allografts and alloplasts or a combination between them has been demonstrated to be effective for increasing bone height and bone volume in the deficient posterior maxilla. PURPOSE: The aim of this clinical trial is to comparatively determine the density of newly formed in sinus floor augmentation bone after a 24-week healing period treatment with a new bovine xenograft. MATERIALS AND METHODS: The sinus floor was grafted with Bio-Oss® (n = 10) and Osseous® (n = 10). Histological sections were examined with a focus on the presence of connective tissue (CT) and newly formed bone (NFB). The sections were histomorphometrically evaluated and the definitive crown was inserted after 3 months. RESULTS: After 6 months, the mean value of new bone formation was 24.60 (±2.503), the CT was 42.60 (±4.006) and the remaining biomaterial was 25.40 (±2.547) in Bio-Oss group. In Osseous group, the mean value of new bone formation was 24.90 (±3.542), the CT was 45.70 (±7.040) and the remaining biomaterial was 22.90 (±3.247). CONCLUSIONS: Both biomaterials afforded a favorable implant position and the prosthetic rehabilitation.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".