Alveolar bony crest preservation at implants installed immediately after tooth extraction: an experimental study in the dog
Bibliographic record
Abstract
AIM: To evaluate the influence of deproteinized bovine bone mineral in conjunction with a collagen membrane, at implants installed into sockets in a lingual position immediately after tooth extraction, and presenting initial horizontal residual buccal defects <2 mm. MATERIAL AND METHODS: The pulp tissue of the mesial roots of (4)P(4) was removed in six Labrador dogs, and the root canals were filled with gutta-percha and cement. Flaps were elevated, and the buccal and lingual alveolar bony plates were exposed. The premolars were hemi-sectioned, and the distal roots were removed. Implants were installed in a lingual position and with the margin flush with the buccal bony crest. After installation, defects resulted at about 1.7 mm in width at the buccal aspects, both at the test and control sites. Only in the left site (test), deproteinized bovine bone mineral (DBBM) particles were placed into the defect concomitantly with the placement of a collagen membrane. A non-submerged healing was allowed. RESULTS: After 3 months of healing, one implant was found not integrated and was excluded from the analysis together with the contralateral control implant. All remaining implants were integrated into mature bone. The bony crest was located at the same level of the implant shoulder, both at the test and control sites. At the buccal aspect, the most coronal bone-to-implant contact was located at a similar distance from the implant margin at the test (1.7 ± 1.0 mm) and control (1.6 ± 0.8 mm) sites, respectively. Only small residual DBBM particles were found at the test sites. CONCLUSION: The placement of an implant in a lingual position into a socket immediately after tooth extraction may favor a low exposure of the buccal implant surface. The use of DBBM particles, concomitantly with a collagen membrane, did not additionally improve the outcome obtained at the control sites.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".