DEVS as a Semantic Domain for Programmed Graph Transformation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This chapter shows how the Discrete EVent system Specification (DEVS) can be used as a semantic domain for the control structures in a model/graph transformation system. It introduces people running example, an extended version of a recent benchmark for graph transformation. The chapter shows how extending the metamodel of DEVS allows for the introduction of programmed model/ graph transformation. It illustrates a solution to the case study problem using that transformation language. The chapter shows how the notion of time can elegantly be added to a transformation ultimately allowing real-time deployment using the notion of time inherent in DEVS. It compares people DEVS-based approach to other graph transformation approaches. The chapter also shows how the modularity and expressiveness of DEVS allow for elegant encapsulation of model transformation building blocks. For the simulation experiments, an initial model was used with the following setup: eight nodes, one hill, and one node counter and no ants.
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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 | 0.001 | 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