Computer guided sinus floor elevation through lateral window approach with simultaneous implant placement
Bibliographic record
Abstract
BACKGROUND: The introduction of CAD/CAM technology in implant dentistry has marked a new era, allowing various procedures to be carried out with a level of great precision and accuracy. PURPOSE: The aim of the present study is to compare the efficacy of a CAD/CAM generated surgical cutting guide in the reduction of incidence of membrane perforation during maxillary sinus floor elevation in relation to the standard lateral window approach technique. MATERIALS AND METHODS: Twenty cases of maxillary sinus elevation were randomly divided into 2 groups. The first group received computer guided sinus floor elevation through lateral window approach and simultaneous implant placement while the second group received standard sinus elevation procedure through lateral window approach with simultaneous implant placement. RESULTS: In the computer guided group, 3 out of 10 cases presented with sinus septa, only 1 case suffered from membrane perforation during the elevation process. In the non-guided group, 3 cases suffered from membrane perforation, 2 of which were complicated by sinus septa. CONCLUSION: Within the limits of this study, computer guided sinus floor elevation showed promising results in accurately modifying the lateral window osteotomy and presents as a safe alternative to the standard technique.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".