A prospective randomized controlled trial of two‐window versus solo‐window technique by lateral sinus floor elevation in atrophic posterior maxilla: Results from a 1‐year observational phase
Bibliographic record
Abstract
BACKGROUND: Implant failures are more common when multiple missing posterior teeth need lateral sinus floor elevation owing to inadequate tissue maturation after grafting. Effects of lateral window dimensions on vital bone formation have rarely been compared. PURPOSE: To compare endo-sinus bone formation between two- and solo-window techniques to rehabilitate multiple missing posterior teeth that need substantial augmentation. METHODS AND MATERIALS: Patients with severely atrophic posterior maxilla were randomized to receive lateral sinus floor elevation via solo or two bony windows. Bone core specimens harvested from lateral aspect of the augmentation sites were histomorphometrically analyzed. Proportions of mineralized bone (MB), bone substitute materials (BS), and nonmineralized tissue (NMT) were quantified. RESULTS: in the test and control groups, respectively. Histomorphometric analysis revealed mean MB of 42.32% ± 13.07% and 26.00% ± 15.23%, BS of 40.34% ± 9.52% and 60.03% ± 10.13%, and NMT of 18.14% ± 14.24% and 14.75% ± 10.38% in test and control groups, respectively, with significant differences. CONCLUSION: The two-window technique could facilitate faster maturation and consolidation of the grafted volume and is an effective alternative for rehabilitation of severely atrophic posterior maxilla with multiple missing posterior teeth.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".