Integrating System Dynamics with System Modeling Language for Resilient System Design
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
Abstract Resilience engineering requires robust methodologies to model and predict system behavior under adverse conditions. While the Systems Modeling Language is excellent for designing system structures, it cannot simulate dynamic behavior over time. System Dynamics focuses on feedback loops, stocks, and flows, providing a simulation‐based approach to modeling such behavior. This paper examines the integration of System Dynamics with System Modeling Language to enhance resilience modeling. It emphasizes potential benefits, challenges, and future research opportunities. By examining the methodologies, mapping their elements, and considering implementation strategies, the paper aims to provide a framework for systems engineers seeking to design resilient systems capable of avoiding, withstanding, and recovering from adversities.
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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