Correlation between Trochlear Dysplasia and the Notch Index
Bibliographic record
Abstract
PURPOSE: To evaluate the correlation between trochlear dysplasia and the notch index. METHODS: Magnetic resonance images (MRI) of 95 knees in 54 male and 36 female patients aged 4 to 74 (mean, 28) years were reviewed by 2 musculoskeletal radiologists. Standard MRI sequences were used. Based on the Dejour classification of trochlear dysplasia, the knees were classified into normal or types A, B, C, and D. A notch index of <0.2 was considered narrow. Normal knees and knees with trochlear dysplasia were compared. RESULTS: 60 of the 95 knees had trochlear dysplasia, of which 39 were Dejour type A, 13 were type B, 7 were type C, and one was type D. Dejour types B, C, and D were combined as non-type A. Inter-observer agreement in assessing the notch index was good (Kappa=0.6). The mean notch indices in normal knees and knees with trochlear dysplasia were comparable (0.161 vs. 0.157, p=0.18), as were in Dejour type A and non-type A knees (0.154 vs. 0.160, p=0.54) and in Dejour types A, B, C, and D knees (0.154 vs. 0.165 vs 0.153 vs. 0.2, p=0.17-0.7). The rate of ACL injuries was similar in patients with normal knees and those with type-A trochlear dysplasia. A low notch index (narrow notch) was not associated with ACL injury. CONCLUSION: The notch index and trochlear morphology are 2 independent entities. A narrow notch does not imply a shallow trochlear grove.
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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) | 0.000 | 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".