Randomized clinical trial for the biological evaluation of two nanostructured biphasic calcium phosphate biomaterials as a bone substitute
Bibliographic record
Abstract
BACKGROUND: The presence of nonresorbable residual granules of hydroxyapatite (HA) may decrease the bone/implant interface. To balance resorption and bone formation biphasic calcium phosphate ceramics compounds applied at different rates have been studied. PURPOSE: The aim of this trial was to compare the clinical, histological, and histomorphometric responses of two new biphasic calcium phosphate biomaterials in fresh dental sockets after 3 and 6 months. MATERIALS AND METHODS: Forty-eight volunteers were divided randomly and double-blindly into 4 groups of 12 individuals: Clot (C), BoneCeramic (BC), Biomaterial 1 (B1), and Biomaterial 2 (B2) groups. Three and six months later, samples were obtained, and histological and histomorphometric sections were evaluated, focusing on the presence of fibrous connective tissue (CT) and newly formed bone. Statistical analysis was performed (P < .05%). RESULTS: The quantification of crystalline phases showed B1 composed of HA (60.28%) and β-TCP (39.72%); B2 composed of HA (78.21%) and β-TCP (21.79%); and BC composed of HA (61%) and β-TCP (39%). The B1 group showed the most newly formed bone (69.3% ± 6.03%), followed by the BC (51.6 ± 12.34%), B2 (46.6 ± 7.66%), and C groups (45.4 ± 7.98%), and less connective tissue and biomaterial remained in the B1 group after 6 months. CONCLUSION: B1 group showed the greatest amount of newly formed bone after 6 months.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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; 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".