Nonlinear finite element-based modeling of soft-tissue cutting
Bibliographic record
Abstract
This paper concerns with nonlinear modeling of biological soft-tissue cutting for simulation and planning of medical procedures. The complicated mechanical behavior of soft-tissue is modeled by considering both geometrical and material nonlinearities using an Ogden-based constitutive equation. The incompressible property of soft-tissue material during deformation is enforced and the Finite Element Method is utilized to discretize the deformable object model in the spatial domain. Element separation and node snapping are used to create a cut in the mesh that is as close as possible to the tool trajectory while preserving the mass of the object and the number of elements in the mesh. In addition, an algorithm is proposed to ensure that the cutting technique guarantees a minimum mesh quality and hence simulation stability by remeshing few elements in the cut area only when needed. Numerical simulations have been carried out in order to evaluate the effectiveness of the proposed modeling techniques.
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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".