Computational biomechanics of knee joint in open kinetic chain extension exercises
Bibliographic record
Abstract
Open kinetic chain (OKC) extension exercises are commonly performed to strengthen quadriceps muscles and restore joint function in performance enhancement programs, in exercise therapies and following joint reconstruction. Using a validated 3D nonlinear finite element model, the detailed biomechanics of the entire joint in OKC extension exercises are investigated at 0, 30, 60 and 90 degrees joint angles. Two loading cases are simulated; one with only the weight of the leg and the foot while the second considers also a moderate resistant force of 30 N acting at the ankle perpendicular to the tibia. The presence of the 30 N markedly influences the results both in terms of the magnitude and the trend. The resistant load substantially increases the required quadriceps, patellar tendon, cruciate ligaments and joint contact forces, especially at near 90 degrees angles with the exception of ACL force that is increased at 0 degrees angle. At post-ACL reconstruction period or in the joint with ACL injury, the exercise should preferably be avoided at near full extension positions under large resistant forces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".