The methods used for the diagnosis and evaluation of scoliosis
Bibliographic record
Abstract
Abstract In recent years there multiple studies have been carried out on early diagnosis of scoliosis on school and preschool children. The diagnosis and evaluation of scoliosis is done by carrying out X-rays. A protocol is implemented for tracking the evolution of a scoliosis which involves both clinical control and imaging (X-ray) every 6 months, until the end of the growth period of the child. Because investigations such as X-ray and CT, can have harmful effects on the child's growing body (recent studies have shown that X-ray affects the skin, eyes, hematopoietic tissue, gonads and may cause cancer), new methods for diagnosing and tracking the evolution in time were researched. The present paper tries to present the current methods used in the diagnosis and assessment of scoliosis evolution in time, pointing out the main advantages and disadvantages of each method. There are a few methods developed in recent years in Germany by Zebris Medical Gmbh (using mapping with ultrasonic digital equipment), in Canada by InSpeck (using three-dimensional mapping through digital image acquisition) but used on a small scale. The newly developed methods have the advantage of being non-invasive, painless, non-irradiating and they can be used regardless of health status or gender. Although medical technology has developed very rapidly in recent years, radiology remains the most common method of investigation used for scoliosis. Certainly, in the near future the methods presented in this paper could be used more widely, for the benefits arising from their use.
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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 | 0.002 | 0.002 |
| 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 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".