Quantification of In Vivo Laxity in the ACL and Individual Knee Joint Structures
Bibliographic record
Abstract
In biomechanical terms, passive joint laxity is a measure of joint movement within the constraints of ligaments, capsule, and cartilage [1] when an external force is applied to the joint during a state of muscular relaxation. Excessive knee joint laxity (reduced stiffness) can result from soft tissue injury, such as a ligament tear, or from genetic factors such as benign joint hypermobility syndrome, and can predispose the joint to instability including recurrent dislocations, and low-grade inflammatory arthritis [2]. A novel technique for in vivo measurement of 3D knee joint laxity using magnetic resonance (MR) imaging with a custom knee loading apparatus (KLA) has been developed in our research group [3]. Gross joint laxity is predicted based on joint displacement in response to an applied anterior tibial load. To better understand the link between laxity and instability, and to advance this technique for clinical applications, the laxity of individual joint structures, such as the anterior cruciate ligament (ACL) must be quantified.
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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".