Canonical Correlations Between Body Posture Variables and Postural Stability in Children with Scoliosis and Scoliotic Posture
Bibliographic record
Abstract
Background: The aim of the study was to analyse the correlation between body posture variables and postural stability in children with scoliosis and scoliotic posture.Methods: Spinal examination photogrammetry used the photometric Moiré method. Based on the angle size of the of spinal curvature, scoliotic posture was determined: 1-9°, and scoliosis: ≥10°. Postural reactions were tested using the Tecnobody ST 310 Plus Stability System platform. Children attended therapy at the Inter-school Centre of Corrective and Compensatory Gymnastics in Starachowice The study was conducted in June 2011. There were 21 children with scoliotic posture (7%) and 7 with scoliosis (25%). Results: In the canonical analysis of body posture variables, the highest share comprised of: trunk inclination angle, alpha angle, chest kyphosis angle, length of lumbar lordosis, length of lumbar lordosis/total spine length, shoulder asymmetry – right higher, shoulder asymmetry – left higher, absolute of pelvis tilt angle, coefficient of shoulder asymmetry relative to C7, primary curvature angle, length of secondary curvature/total spine length, depth of secondary curvature/total spine length. Significance: High values of canonical correlation coefficients, despite lack of significance, indicate the possibility of strong a correlation between body postural variables and postural stability that can be demonstrated with a greater sample size.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".