A Modeling Study of Partial ACL Injury: Simulated KT-2000 Arthrometer Tests
Bibliographic record
Abstract
A partial ACL injury may involve different levels of fiber disruption, orfibers may sustain microscopic changes in their structure without gross disruption, resulting in a change in ligament function. The effect of partial ACL tears on the mechanical and functional stability of the knee has not been well documented, in part because of diagnostic difficulties. A computer model of the knee in the sagittal plane was used in this study to simulate tests using the KT-2000 Knee Arthrometer, which quantifies Lachman's test for ACL injury. A variety of partial ACL anterior and posterior bundle injuries were simulated. Anterior and posterior bundle injuries were subdivided into four different simulated injury levels: mild (one-half tear of the bundle), moderate (complete tear of the bundle), severe (complete tear of the bundle and tear of one-half of the other bundle), and more severe (severe injury plus an additional elongation of the other bundle represented by 5% increases of its initial strain). Force-displacement results obtained from simulated KT-2000 knee arthrometer tests depended on the level of injury. Mild and moderate injuries produced only small change in the anterior tibial translation--at different force levels. Severe injury produced increased anterior tibial translation depending on which bundle was completely ruptured. The compliance index defined as the ratio of the displacement and the force within 68 N and 90 N anterior drawer forces, the stiffness, and the rate of change of stiffness of the anterior force-displacement were found to be better at predicting partial ACL ruptures than simple differences in anterior tibial translation. It was possible in the model results to discriminate knees with various levels of partial ACL injuries using the first and second derivatives of the force-displacement curve.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".