<scp>B</scp>one <scp>C</scp>eramic® at Implants Installed Immediately into Extraction Sockets in the Molar Region: An Experimental Study in Dogs
Bibliographic record
Abstract
PURPOSE: The aim of this paper was to study the healing of 1-1.4 mm wide buccal defects at implants placed immediately into extraction sockets (IPIES) filled with a mixture of synthetic hydroxyapatite (HA) 60% and beta-tricalciumphosphate (TCP) 40% or left with the clot alone and both covered with collagen membranes. MATERIAL AND METHODS: Eight Labrador dogs were used and implants were placed immediately into the extraction sockets of the first molar bilaterally. A mixture of synthetic HA 60% and beta-TCP 40% at the test or the clot alone at the control sites were used to fill the defects. All surgical sites were subsequently covered by a resorbable collagen membrane and a non-submerged healing was allowed. After 4 months, the animals were euthanized, biopsies harvested and processed for histomorphometric analysis. RESULTS: At the time of installation, residual buccal defects occurred that were 1.1 mm and 1.4 mm wide and 3 mm and 4 mm deep at the control and test sites, respectively. After 4 months of healing, the top of the bony crest and the coronal level of osseointegration were located respectively at 0.1 ± 1.8 mm and 1.5 ± 1.8 mm at the test, and 0.6 ± 1.6 mm and 1.2 ± 0.7 mm at the control sites apically to the implant shoulder. Bone-to-implant contact at the buccal aspect was 34.9 ± 25.9% and 36.4 ± 17.3% at the test and control sites, respectively. No statistically significant differences were found between test and control sites for any of the variables analyzed at the buccal aspects. CONCLUSIONS: The use of a mixture of synthetic HA 60% and beta-TCP 40% to fill residual buccal defects 1-1.4 mm wide at IPIES did not improve significantly the results of healing.
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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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".