Development of a multibody model to assess efforts along the spine for the rehabilitation of adolescents with idiopathic scoliosis.
Bibliographic record
Abstract
INTRODUCTION: Gait analysis has often been recognized as helpful for the therapeutic follow-up of adolescents with idiopathic scoliosis (IS). METHODS: A multibody model of the human body was developed to display the intervertebral efforts along the spine of each adolescent with IS, and highlight the efforts that significantly differ from typical age-matched healthy adolescents. The intervertebral efforts of one adolescent with IS and an age-matched adolescent during a complete gait cycle were computed and compared. RESULTS: All intervertebral efforts are larger in the adolescent with IS compared to the healthy adolescent, except for the vertical torque. The average medio-lateral torque and force for the participant with IS are respectively 200% and 114% higher. CONCLUSION: This study revealed that the pathological efforts are not concentrated around critical points but distributed along the spine. Thus, higher average efforts along the spine in adolescent with IS may influence the spine deformity due to mechanical modulations according to the Hueter-Volkmann Law. The potential of this model is promising for the therapeutic follow-up of adolescents with IS because it provides real-time efforts along the spine, as well as the corresponding information about the asymmetrical behavior of the spine during gait.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".