Flap vs. “flapless” surgical approach at immediate implants: a histomorphometric study in dogs
Bibliographic record
Abstract
Abstract Aim: To compare the remodeling of the alveolar process at implants installed immediately into extraction sockets by applying a flap or a “flapless” surgical approach in a dog model. Material and methods: Implants were installed immediately into the distal alveoli of the second mandibular premolars of six Labrador dogs. In one side of the mandible, a full‐thickness mucoperiosteal flap was elevated (control site), while contra‐laterally, the mucosa was gently dislocated, but not elevated (test site) to disclose the alveolar crest. After 4 months of healing, the animals were sacrificed, ground sections were obtained and a histomorphometric analysis was performed. Results: After 4 months of healing, all implants were integrated (n=6). Both at the test and at the control sites, bone resorption occurred with similar outcomes. The buccal bony crest resorption was 1.7 and 1.5 mm at the control and the test sites, respectively. Conclusions: “Flapless” implant placement into extraction sockets did not result in the prevention of alveolar bone resorption and did not affect the dimensional changes of the alveolar process following tooth extraction when compared with the usual placement of implants raising mucoperiosteal flaps. To cite this article: Caneva M, Botticelli D, Salata LA, Souza SLS, Bressan E, Lang NP. Flap vs. “flapless” surgical approach at immediate implants: a histomorphometric study in dogs. Clin. Oral Impl. Res. 21, 2010; 1314–1319. doi: 10.1111/j.1600‐0501.2009.01959.x
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".