A Dynamic Jaw Model With a Finite-Element Temporomandibular Joint
Bibliographic record
Abstract
joint force measurements are not feasible to directly test this assumption. Consequently, biomechanical computer simulation remains as one of a few means to investigate this complex system. To thoroughly examine orofacial biomechanics, we developed a novel, dynamic computer model of the masticatory system. The model combines a muscle driven rigid body model of the jaw region with a detailed finite element model (FEM) disk and elastic foundation (EF) articular cartilage. The model is validated using high-resolution MRI data for protrusion and opening that were collected from the same volunteer. Joint stresses for a clenching task as well as protrusive and opening movements are computed. Simulations resulted in mandibular positions as well as disk positions and shapes that agree well with the MRI data. The model computes reasonable disk stress patterns for dynamic tasks. Moreover, to the best of our knowledge this model presents the first ever contact model using a combination of EF layers and a FEM body, which results in a clear decrease in computation time. In conclusion, the presented model is a valuable tool for the investigation of the human TMJ and can potentially help in the future to increase the understanding of the masticatory system and the relationship between TMD and joint stress and to highlight potential therapeutic approaches for the restoration of orofacial function.
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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 | 0.000 | 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 | 0.001 |
| 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".