Healing at implants placed in bone of different morphology: an experimental study in dogs
Bibliographic record
Abstract
OBJECTIVE: To study osseointegration at implants installed using a standard bed preparation in sites of different bone morphology. MATERIAL AND METHODS: In six Labrador dogs, all mandibular premolars and first molars were extracted. After 4 months of healing, flaps were elevated, and two recipient sites were prepared in each side of the mandible, one in the second premolar and the other in the molar regions. Bone morphology and final insertion torque were evaluated. Healing abutments were applied, and the flaps were sutured to allow a non-submerged healing. After 4 months, the animals were sacrificed and ground sections were obtained for histomorphometric analyses. RESULTS: At the premolar sites, bone morphology Class 2 and at the molar regions Class 3 or 4 were identified. The final insertion torque was 50-55 Ncm at the premolar and 30-35 Ncm at the molar sites. Mean osseointegration in percentage reached 61.5 ± 11.5% and 63.3 ± 10.1% at the premolar and molar sites, respectively. Mineralized bone density evaluated from the implant surface up to a distance of about 0.6 mm lateral to the implant surface was 63.0 ± 7.4% and 65.4 ± 17.7% at the premolar and molar sites, respectively. CONCLUSIONS: Similar implant bed preparations performed at premolar and molar sites with different bone morphology, yielding insertion torque values of about 30-35 and 50-55 Ncm, respectively, did not affect osseointegration after 4 months at non-submerged implants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".