Detection of early osteoarthritis in canine knee joints 3 weeks post ACL transection by microscopic MRI and biomechanical measurement
Bibliographic record
Abstract
Purpose: To detect early osteoarthritis (OA) in a canine Pond–Nuki model 3 weeks after anterior cruciate ligament (ACL) transection surgery, both topographically over the medial tibial surface and depth-dependently over the cartilage thickness. Methods: Four topographical locations on each OA and contralateral medial tibia were imaged individually by magnetic resonance imaging (MRI) at 17.6 µm transverse resolution. The quantitative MRI T 2 relaxation data were correlated with the biomechanical stress-relaxation measurements from adjacent locations. Results: OA cartilage was thinner than the contralateral tissue and had a lower modulus compared to the contralateral cartilage for the exterior, interior, and central medial tibia locations. Depth-dependent and topographical variations were detected in OA cartilage by a number of parameters (compressive modulus, glycosaminoglycan concentration, bulk and zonal thicknesses, T 2 at 0° and 55° specimen orientations in the magnet). T 2 demonstrated significant differences at varying depths between OA and contralateral cartilage. Conclusion: ACL transection caused a number of changes in the tibial cartilage at 3 weeks after the surgery. The characteristics of these changes, which are topographic and depth-dependent, likely reflect the complex degradation in this canine model of OA at the early developmental stage.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".