Evaluation of the Clinical Significance of Classification of Traumatic Anterior Shoulder Instability Using Double-Contrast Computed Tomography Arthrography
Bibliographic record
Abstract
This study evaluated the clinical significance of traumatic anterior shoulder instability (TASI) classification using double-contrast computed tomography (CT) arthrography. Patient were randomly assigned to two groups: group 1 (n = 62); and group 2 (n = 63). TASI symptom severity in group 1 was assessed using physical signs of shoulder trauma and conventional X-ray, CT and magnetic resonance imaging; these patients received either conservative management (with physical rehabilitation) or standard surgery. Group 2 underwent double-contrast CT arthrography to classify TASI; its findings formed the basis of subsequent management. At 24 months post-therapy, significant improvements in clinical outcomes were observed in group 2: Constant scores were higher and Western Ontario Shoulder Instability Index scores were lower. At 24 months, recurrence rates were 21.0% (13/62) in group 1 and 7.9% (5/63) in group 2. Findings suggested that TASI classification using double-contrast CT arthrography provided meaningful information thereby improving treatment efficacy.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".