Humeral Head Posterior Subluxation on CT Scan: Validation and Comparison of 2 Methods of Measurement
Bibliographic record
Abstract
Background Humeral static posterior translation is important for evaluation of osteoarthritis. Two different methods are compared for absolute difference and reliability. Methods A group of patients with shoulder pathology were analyzed. Images were evaluated 2 times with 2 methods by 3 evaluators. The first method, scapula method (SM), uses the scapula axis as a reference line (line drawn from the medial border of the scapula body to the center of the glenoid). The second method, named mediatrice method (MM), used the “mediatrice” line, drawn as a perpendicular line to glenoid joint surface passing in its middle. The percentage of the humeral head posterior to the line was assessed at the longest AP diameter. A percentage higher than 55% defined posterior subluxation. Reliability of both methods was obtained using consistency and interobserver agreement using intraclass correlation. Results One hundred fifteen cases met the inclusion criteria. The intraobserver reliability was very good using SM and good with MM. The interobserver reliability was very good for SM and good for MM. Conclusion The SM is slightly more reliable for subluxation measurement of the glenohumeral joint, however, both could be used to study the influence of humeral head subluxation on postoperative results.
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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 | 0.018 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".