MODELING OF KNEE ARTICULAR CARTILAGE DISSIPATION DURING GAIT ANALYSIS
Bibliographic record
Abstract
Articular cartilage dissipates contact loads according to three dissipative mechanisms: frictional drag, intrinsic viscoelasticity, and surface friction. Estimation of dissipation due to these three mechanisms during gait is required to understand the dissipative properties of articular cartilage. Fourteen healthy subjects performed a gait analysis on treadmill. Tibiofemoral contact forces were estimated from inverse dynamic analysis and from a reductionist knee contact model. These contact forces and the results obtained from a preloading creep simulation were introduced into a biphasic poroviscoelastic articular cartilage model, and a one-dimensional confined compression was performed. Articular dissipation from each dissipative mechanism was estimated. Sensitivity analysis was performed to determine the effects of material parameters and length of the preloading simulation on the patterns of the dissipative mechanisms. Dissipative force patterns for all dissipative mechanisms were found to be similar to those of tibiofemoral contact forces. Frictional drag was found to be the dominant dissipative mechanism. The initial permeability and the viscoelastic spectrum parameters were found to have an important impact on the magnitude of the peaks of dissipative patterns. If appropriate material parameters are introduced, this model could be used to compare the difference between healthy and osteoarthritic human articular cartilage.
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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) | 0.001 | 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) | 0.000 | 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".