Bone‐implant‐contact and new bone formation around implants placed in FDB blocks compared to placement at the adjunction of particulate FDB
Bibliographic record
Abstract
BACKGROUND: The efficacy of human freeze-dried bone (h-FDB) as particulate vs block forms as a proper onlay augmented bone graft material to accommodate implants is undetermined. PURPOSE: To evaluate osseointegration and new bone formation at implants placed in FDB blocks (BL group) and those at the adjunction of particulate FDB (PR group). MATERIALS AND METHODS: Twelve pairs of h-FDB blocks were stabilized bilaterally to the calvaria of 12 rabbits. Twenty-four SLA implants were placed at the remodeled grafted blocks, 4 months later. A circumferential gap was created around one implant in each pair and packed with particulate h-FDB. Section biopsies were obtained at 2-month post implant placement (6 months post-block grafting). Bone-to-implant contact (BIC) and bone-area fraction (BAF) were histomorphometrically calculated. RESULTS: The mean BIC was 34.4% and 33.5% for the BL and PR groups, respectively. The mean BAF was 23.9% and 26.4% for the corresponding groups, respectively. Osseointegration and newly formed bone were evident mostly between the threaded portions of the implants in proximity to the host rabbit calvaria compared to its cervical neck. CONCLUSION: The particulate and the cancellous block h-FDB forms yielded similar BIC and BAF outcome. Full revascularization/revitalization is questioned.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".