Explicit modelling of statechart simulation environments
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
In this paper, we propose an experimentation environment for the interactive simulation of Statechart models. We choose the Statecharts formalism as the most appropriate formalism to model and synthesize the environment. We take inspiration from software debugging as well as from simulation experimentation to explicitly model the detailed reactive behaviour of our environment. We map program debugging techniques such as execution modes, steps, and breakpoints to the simulation domain. We further explore how to integrate the notion of simulation time for the purpose of (scaled) real-time visualisation. Finally, we provide support for a (browser)clientserver architecture, again making use of the features of Statecharts. We build the experimentation model on top of the model to be simulated by instrumenting it using model transformation techniques. The entire Statechart modelling, simulation, and experimentation environment described in this work is supported by our tool, AToMPM. 1.
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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