Arthroscopic Posterior Glenoid Augmentation With a Fresh Distal Tibia Allograft
Bibliographic record
Abstract
Recurrent posterior instability, resulting in posterior glenoid bone loss, or significant posterior glenoid bone loss at the index procedure can be a cause of failure of arthroscopic posterior stabilization repair. There are several described autograft and allograft options to restore posterior glenoid bone stock if the posterior glenoid bone loss is significant, generally greater than 20% of the surface of the glenoid. Advantages of a fresh distal tibia allograft include a contour near anatomic to the native glenoid with an articular surface that matches the humeral head through arc of motion and no associated donor site morbidity. This technique article outlines an approach to a failed arthroscopic posterior capsulolabral repair with an arthroscopic fresh distal tibia osteochondral allograft for recurrent posterior shoulder instability in the setting of glenoid bone loss.
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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 | 0.000 | 0.000 |
| 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".