Static and dynamic guided bone regeneration using a shape‐memory polyethylene terephthalate membrane: An experimental study in rabbit mandible
Bibliographic record
Abstract
BACKGROUND: Periosteal expansion (PEO) results in the formation of new bone in the space created between existing bone by expanding the periosteum. PEO has already been performed on rabbit parietal bone and effective new bone formation has been demonstrated. In this study, the utility of a polyethylene terephthalate (PET) membrane as an activator was evaluated in the more complex morphology of the mandible. METHODS: A PET membrane coated with hydroxyapatite (HA)/gelatine was placed in the rabbit mandibular bone at lower margin of mandibular molar region underneath periosteum, and screw-fixed. In the experimental group, the membrane was bent and screw-fixed along the lateral surface of the bone, with removal of the outer screw after 7 days followed by activation of the membrane. The experimental group was divided into two subgroups: with and without a waiting period for activation. Three animals were euthanized at 3 weeks and another three at 5 weeks postoperatively. Bone formation was assessed using micro-CT as well as histomorphometric and histological methods. RESULTS: No PET membrane-related complications were observed. The area of newly formed bone and the percentage of new bone in the space created by the stretched periosteum did not significantly differ between the control and experimental groups. However, in the experimental group a greater volume was present after 5 weeks than after 3 weeks. Histologically, bone formation occurred close to the site of cortical bone perforation, with many sinusoidal vessels extending through the perforations in the new bone into the overlying fibrous tissue. Inflammatory cells were not seen in the bone.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".