Application of a Novel Measure of In Vivo Knee Joint Laxity
Bibliographic record
Abstract
Current measures of knee joint laxity, such as those found clinically using the KT-2000 arthrometer, are not highly repeatable or reliable by Huber et al. (1997, "Intratester and Intertester Reliability of the KT-1000 Arthrometer in the Assessment of Posterior Laxity of the Knee," Am. J. Sports Med., 25(4), pp. 479-485). In this study, a noninvasive in vivo magnetic resonance (MR) imaging-based measure of laxity, the knee loading apparatus (KLA) with anterior positioning frame, was evaluated with five normal subjects (repeatability study, n = 3). Effects of hormones and muscle guarding were considered. When compared to the KT-2000, the KLA was found to be more precise (±0.33 mm versus ±1.17 mm) but less reliable (Cronbach's alpha > 0.70 in 0/8 versus 5/8 load levels). Improved control of the initial subject position is recommended for future design iterations. The KLA shows promise as an accurate and reliable tool for measuring in vivo joint and ligament laxity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".