Finite element representation of bone substitute remodelling in the jaw bone
Bibliographic record
Abstract
The finite element (FE) method was originally developed on a physical basis for the computation of structure-mechanical problems. Meanwhile, it has been widely applied to medical issues. This study sought a suitable method to build a FE model for remodelling processes in osseous defects supplemented with bone substitute material. For this purpose, the second right premolars were extracted from four pig mandibles (Sus scrofa domesticus) and the extraction alveoli were provided with synthetic bone substitute material. After 70 days, a segmented osteotomy of this area was performed for specimen collection. Radiographs of the specimens were taken in defined planes before and after fixation and embedded with Technovit 9100. Fixation-related shrinkage was quantified from the radiographs using reference lines. Computer tomographic (CT) and microCT images of the fixed and embedded specimens were obtained. From these data, a FE model was built. The construction of a FE model is sufficient to represent bone remodelling after supply of bone substitute material. The use of microCT data permits building a clearly more precise 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 | 0.000 | 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 | 0.001 | 0.000 |
| 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".