DEVS-based design of spatial simulations of biological systems
Why this work is in the frame
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Bibliographic record
Abstract
The application of the DEVS formalism to spatial simulations of biological systems is motivated by a need to keep software manageable, even when faced with complex models that may combine algorithms for potential fields, fluid dynamics, the interaction of proteins, or the reaction and diffusion of chemicals. We demonstrate DEVS-based design by applying the formalism to a ¿tethered particle system¿ (TPS), a model we designed to capture the motion of deformable biological structures. The paper focuses on the design of DEVS models using hierarchies and layers, and describes a recently-developed simulator that supports our approach. The DEVS-based TPS model, which has been used to simulate certain interactions in nerve cells, demonstrates the formalism's potential as a means of addressing the complexity of spatial biological models.
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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 it