Re-positioning effects of a full torso imaging system for the assessment of scoliosis
Bibliographic record
Abstract
The effect of re-positioning (sway and breathing) on the reproduction accuracy of a low-cost torso imaging system for monitoring idiopathic scoliosis is assessed. The system utilizes a rotating positioning frame and a 3D digitizer. Four images taken at 90 degree intervals are needed to generate a torso image. Five volunteers having no scoliosis were used for the study. Four torso images of each volunteer were obtained. Ten evenly-spaced cross-sections are computed for each torso image. The distance between the centroids of successive cross-sections and a reference vertical axis are computed at each cross-section. The standard deviation of this distance at each cross-section is indicative of the variability due to sway. The variability due to breathing is assessed by computing the standard deviation of the widths and lengths of each cross-section for each volunteer. Results obtained indicate that the torso imaging system is adequate for assessing idiopathic scoliosis.
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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 | 0.001 | 0.009 |
| 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".