Rotator Cuff Injury and Repair
Bibliographic record
Abstract
Rotator cuff pathology is a commonly encountered clinical and radiologic entity that can manifest as tendinopathy or tearing. Magnetic resonance imaging (MRI) and ultrasonography offer similar sensitivity and specificity for the evaluation of the native rotator cuff, and the chosen modality may vary, depending on local practice and accessibility. MR arthrography is frequently used in the postoperative setting as a problem-solving tool. Key findings to include in the preoperative MRI report include the size and location of the tear, thickness of the tendon involved (partial versus full thickness), and overall tendon quality. The report should also address features associated with poor surgical outcomes, such as fatty atrophy, a decreased acromiohumeral interval, and evidence of rotator cuff arthropathy. Musculoskeletal radiologists should be familiar with the various surgical techniques and expected postoperative imaging appearance of rotator cuff repairs. Imaging also plays a role in identifying recurrent tearing, graft failure, hardware loosening, infection, and other complications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".