A viscoelastic poromechanical model of the knee joint in large compression
Bibliographic record
Abstract
The elastic response of the knee joint in various loading and pathological conditions has been investigated using anatomically accurate geometry. However, it is still challenging to predict the poromechanical response of the knee in realistic loading conditions. In the present study, a viscoelastic, poromechanical model of the knee joint was developed for soft tissues undergoing large deformation. Cartilages and menisci were modeled as fibril-reinforced porous materials and ligaments were considered as fibril-reinforced hyperelastic solids. Quasi-linear viscoelasticty was formulated for the collagen network of these tissues and nearly incompressible Neo-Hookean hyperelasticity was used for the non-fibrillar matrix. The constitutive model was coded with a user defined FORTRAN subroutine, in order to use ABAQUS for the finite element analysis. Creep and stress relaxation were investigated with large compression of the knee in full extension. The contact pressure distributions were found similar in creep and stress relaxation. However, the load transfer in the joint was completely different in these two loading scenarios. During creep, the contact pressure between cartilages decreased but the pressure between cartilage and meniscus increased with time. This led to a gradual transfer of some loading from the central part of cartilages to menisci. During stress relaxation, however, both contact pressures decreased monotonically.
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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".