Finite element modeling of vertebral body stapling applied for the correction of idiopathic scoliosis: preliminary results
Bibliographic record
Abstract
Endoscopic vertebral body stapling is an innovative technique intended to treat adolescent idiopathic scoliosis, but the optimal instrumentation design is not yet established. The objective was to simulate the immediate correction obtained from two stapling configurations. A parametric finite element model of a typical right thoracic scoliotic spine (Cobb 21 degrees ) was developed using geometrical and mechanical data from the literature. Staple insertion and closing were modeled. The intra-operative lateral decubitus and standing positions were taken into account. Two implant configurations, varying the number of staples per vertebra, were simulated. The major correction (9 degrees ) came by simulating the intra-operative posture. The immediate Cobb angle correction due to the staples alone was less then 1 degrees for both configurations. However, the staples helped maintain the correction obtained by the intra-operative posture when the post-operative standing position was simulated. Next steps are to validate the model using surgical cases, implement growth modulation modeling, improve lateral decubitus modeling, and analyze different vertebral stapling strategies for different scoliotic curves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".