Biomechanical Modelling of Spinal Growth Modulation for the Study of Adolescent Scoliotic Deformities: A Feasibility Study
Bibliographic record
Abstract
A model of growth modulation was formulated with variables integrating a biomechanical stimulus of growth modulation, a sensitivity factor to the stimulus and time. It was integrated into a finite element model of the thoracic and lumbar spine using an iterative procedure. A simulation on the personalized geometry of a mild scoliotic patient allowed qualitative investigation of scoliotic deformities over 12 cycles (months) in response to a load variation due to an eccentricity of the patient's gravity line in the frontal plane. Resulting frontal, sagittal and transverse spinal views correspond to clinically observable scoliotic configurations. The simulation adequately reproduces a progressing thoracic scoliotic curve while the slight increasing kyphosis represents a possible condition although a thoracic hypokyphosis is frequently reported in the literature. At the thoracic apex, increased wedging as well as axial rotation evolving towards curve convexity are in agreement with clinical and experimental observations reported with curve progression. This study demonstrates the feasibility of the approach and, compared to other biomechanical models, it achieves a more complete representation of the scoliotic spine by incorporating vertebral growth modulation.
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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) | 0.000 | 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) | 0.001 | 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".