Three-dimensional Subclassification of Lenke Type 1 Scoliotic Curves
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Bibliographic record
Abstract
STUDY DESIGN: Prospective study of the 3-D shape variability of spinal curve in Lenke type 1 adolescent idiopathic scoliosis (AIS). OBJECTIVES: To determine the statistical 3-D variability of Lenke type 1 curves and to evaluate clinical parameters that can be integrated to refine the Lenke et al original proposal, and to pave the road for a comprehensive 3-D subclassification of AIS. SUMMARY OF BACKGROUND DATA: Several classification systems based on the identification of key features from frontal and sagittal x-rays have been proposed in AIS, but these remain an oversimplification of the complex 3-D deformity because it is only based on 2-D imaging. Clinical 3-D parameter variability has been investigated in previous studies, but has never been considered in the context of the Lenke classification. METHODS: Radiographs of 68 AIS patients with Lenke type 1 curves were reconstructed in 3-dimension using a stereo-radiographic technique and were submitted to a computer algorithm to compute a set of 3-D parameters that can be used to characterize the 3-D curve. Cluster analysis was performed to determine the statistical distribution of 3-D parameters among Lenke 1 curve types. RESULTS: Statistical analysis shows specific 3-D deformation patterns within Lenke type 1 curves, mostly using the best-fit plane or BFP (SD+/-22.9, +/-49.8) and geometric torsion parameters. No significant variability was found using the plane of maximum curvature or PMC. CONCLUSIONS: Recent advances in computer vision facilitate the introduction of 3-D reconstruction in a standard clinical setting and can provide more information toward the spine behavior in 3-D space. A direct consequence of commonly used 3-D reconstruction would be to be able to evaluate 3-D indices and to devise a real 3-D classification system from the Lenke et al proposal.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it