The Analysis of Selected Posturogram Parameters in Children with Scoliotic Changes
Bibliographic record
Abstract
The aim of the research was to analyze selected posturogram parameters in children with scoliotic changes. 28 girls aged 7-18 years old were involved in the study. Children attended to the Interschool Centre of Corrective Exercises in Starachowice. The research was conducted in June 2011. Spine research was made by Exhibeon digital radiography. Based on the size of the angle of spinal curvature there were identified scoliotic posture: 1-9° and scoliosis: ≥10°. There were 21 (75%) children with scoliotic posture, and 7 (25%) with idiopathic scoliosis. The frequency and type of defect didn't depended on age. Postural reactions were examined by static-dynamic Tecnobody’s ST 310 Plus Stability System platform. Perimeter was from 539,46 with opened eyes (OE) to 759,04 with closed eyes (CE). The difference in Romberg’s Test was 219,58. Ellipse area was from 447,46 with opened eyes (OE) to 850,32 with closed eyes (CE). The difference in Romberg’s Test was 402,86. Perimeter ratio was 146,68, and Area ratio was 213,89. Analysis of variance showed a significant effect of study options which clearly differentiates Permeter (p=0,000008) and Ellipse Area (p=0,029882) in the research with opened and closed eyes. In a study with closed eyes it has been observed a significant increase of posturogram variables. Analysis of variance for Area ratio didn't show any significant effects (p= 0,376899) similarly for Perimeter ratio (p=0,523086). Posturogram variables generally decreased with age, however the analysis of variance didn’t show any statistically significant effects. The analysis of the Spearman rank correlation of posturogram variables with age of examined persons also didn’t show any significant associations.
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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 | 0.002 |
| 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) | 0.001 | 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".