CTM Brace Effect on Scoliotic Intervertebral Discs Using MRI Method
Bibliographic record
Abstract
MRI has been clinically only used for investigation of intervertebral disc disorders. In this study, MR images were used and a new 3D modelling of the intervertebral discs was proposed. MRI examination had been performed on fourteen girls presenting an idiopathic scoliosis and wearing a first CTM brace. Using an in-house image processing software and the pre-post processing software Patran, geometrical models were obtained with and without brace for each patient. These models included the outline of the intervertebral high intensity zone, composed of the nucleus and a part of the annulus. The shift forward between disc high intensity zone centres and body centres was found to be varying from 0 to 8mm. The sagittal and coronal shifts forward appeared in the curvature convexity and were maximum at the curvature apex. The intervertebral disc wedging was found to be varying from -10 degrees to +10 degrees. On these fourteen analysed patients, the CTM brace decreased the coronal shift forward between disc high intensity zone centres and body centres, and increased the sagittal intervertebral wedging. The intervertebral disc informations obtained represented new data in the scoliotic deformation description. But this method was not adapted for a clinical use. The qualitative and quantitative data obtained will help the orthopaedist in the brace design and also the clinician in the scoliosis comprehension.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".