MR imaging of the postoperative knee
Bibliographic record
Abstract
Advances in orthopedic and arthroscopic surgical procedures of the knee such as, knee replacement, ligamentous reconstruction as well as articular cartilage and meniscus repair techniques have resulted in a significant increase in the number of patients undergoing knee arthroscopy or open surgery. As a consequence postoperative MR imaging examinations increase. Comprehensive knowledge of the normal postoperative MR imaging appearances and abnormal findings in the knee associated with failure or complications of common orthopedic and arthroscopic surgical procedures currently undertaken is crucial. This article reviews the various normal and pathological postoperative MR imaging findings following anterior and posterior cruciate ligament, medial collateral ligament and posterolateral corner reconstruction, meniscus and articular cartilage surgery as well as total knee arthroplasty with emphasis on those surgical procedures which general radiologists will likely be faced in their daily clinical routine.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".