Assessment of torso deformities using 3D markerless asymmetry analysis and its clinical applications
Bibliographic record
Abstract
Methods The full torso ST of 90 AIS patients with different curve types were retrieved from our previous study [2]. The mean Cobb angle was 32.5° (range: 8°-69°). The best plane of symmetry that divides the torso into left and right parts was calculated. Deviations between the left and right parts were measured and displayed as deviation colour maps (DCMs). To propose a surface clarification, the DCMs of 46 patients were appraised by three scoliosis professionals. The DCMs were then classified into three main groups and six subgroups by four novice observers. The intra and inter-observer reliability of the classification was assessed using Kappa coefficients. The vertical position of the maximum deviation point above the PSISs was multiplied by a correction factor to estimate the vertical location of the curve apex. Results The mean kappa coefficient for intra-observer reliability was 0.85 (0.68-0.92) indicating good to excellent classification reliability [3]. The inter-observer kappa coefficient was 0.62 and the percentage of agreement was 80%, indicating moderate reliability [3]. For 88 torsos with thoracic curves (subgroups 2, 4 or 5), the location of the point of maximum deviation predicted the location of the curve apex with a ±2.2cm accuracy (range 0.02-5.5cm, R=0.72). For 39 lumbar curves with Cobb angle >20, prediction accuracy was ±1.6cm (0.02-4.2cm; R=0.42).
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".