Knee loading in OA subjects is correlated to flexion and adduction moments and to contact point locations
Bibliographic record
Abstract
Abstract This study evaluated the association of contact point locations with the knee medial and lateral contact force (Fmed, Flat) alterations in OA and healthy subjects. A musculoskeletal model of the lower limb with subject-specific tibiofemoral contact point trajectories was used to estimate the Fmed and Flat in ten healthy and twelve OA subjects during treadmill gait. Regression analyses were performed to evaluate the correlation of the contact point locations, knee adduction moment (KAM), knee flexion moment (KFM), frontal plane alignment, and gait speed with the Fmed and Flat. Medial contact point locations in the medial–lateral direction showed a poor correlation with the Fmed in OA (R2 = 0.13, p = 0.01) and healthy (R2 = 0.24, p = 0.001) subjects. Anterior–posterior location of the contact points also showed a poor correlation with the Fmed of OA subjects (R2 = 0.32, p < 0.001). Across all subjects, KAM and KFM remained the best predictors of the Fmed and Flat, respectively (R2 between 0.62 and 0.69). Results suggest different mechanisms of contact force distribution in OA joints. The variations in the location of the contact points participate partially to explains the Fmed variations in OA subjects together with the KFM and KAM.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".