Ridge preservation at implants installed immediately after molar extraction. An experimental study in the dog
Bibliographic record
Abstract
AIM: To evaluate the influence of deproteinized bovine bone mineral (DBBM), in conjunction with a collagen membrane, on bone resorption at implants installed in a lingual position immediately into extraction sockets with horizontal residual buccal defects >2.0 mm. MATERIAL & METHODS: The pulp tissue of the mesial roots of (1) M(1) was removed in six Labrador dogs, and the root canals were filled with gutta-percha and cement. Flaps were elevated. The molars were hemi-sectioned and the distal roots removed. Implants were installed in a lingual position and with the shoulder flush with the buccal bony crest. After installation, defects of about 2.5 and 2.7 mm in width resulted at the buccal aspects of the test and control sites, respectively. 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. On the control sites, no biomaterials were applied. A non-submerged healing was allowed. RESULTS: After 3 months of healing, one control implant was not integrated and was excluded from the analysis, together with the contralateral test implant. All remaining implants were integrated into mature bone. The buccal alveolar bony crest was resorbed more at the test compared with the control sites, 2.2 ± 0.9 mm and 1.5 ± 1.3 mm, respectively. The vertical resorption of the lingual plate was 1.6 ± 1.5 mm and 1.5 ± 1.1 mm at the test and control sites, respectively. Only small residual DBBM particles were found at the test sites (1.4%). CONCLUSION: The use of DBBM particles to fill buccal defects of ≥2.5 mm at implants installed immediately into alveolar extraction sockets did not preserve the buccal bony wall.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".