Large Bone Vertical Augmentation Using a Three‐Dimensional Printed TCP/HA Bone Graft: A Pilot Study in Dog Mandible
Bibliographic record
Abstract
BACKGROUND: Osteoflux is a three-dimensional printed calcium phosphate porous structure for oral bone augmentation. It is a mechanically stable scaffold with a well-defined interconnectivity and can be readily shaped to conform to the bone bed's morphology. PURPOSE: An animal experiment is reported whose aim was to assess the performance and safety of the scaffold in promoting vertical growth of cortical bone in the mandible. MATERIALS AND METHODS: Four three-dimensional blocks (10 mm length, 5 mm width, 5 mm height) were affixed to edentulous segments of the dog's mandible and covered by a collagen membrane. During bone bed preparation, particular attention was paid not to create defects 0.5 mm or more so that the real potential of the three-dimensional block in driving vertical bone growth can be assessed. Histomorphometric analyses were performed after 8 weeks. RESULTS: At 8 weeks, the three-dimensional blocks led to substantial vertical bone growth up to 4.5 mm from the bone bed. Between 0 and 1 mm in height, 44% of the surface was filled with new bone, at 1 to 3 mm it was 20% to 35%, 18% at 3 to 4, and ca. 6% beyond 4 mm. New bone was evenly distributed along in mesio-distal direction and formed a new crest contour in harmony with the natural mandibular shape. CONCLUSIONS: After two months of healing, the three-dimensional printed blocks conducted new bone growth above its natural bed, up to 4.5 mm in a canine mandibular model. Furthermore, the new bone was evenly distributed in height and density along the block. These results are very promising and need to be further evaluated by a complete powerful study using the same model.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".