Federated critical infrastructure simulators: Towards ontologies for support of collaboration
Bibliographic record
Abstract
Our society relies greatly on a variety of critical infrastructures (CI), such as power system networks, water distribution, oil and natural gas systems, telecommunication networks and others. Interdependency between those systems is high and may result in cascading failures spanning different infrastructures. Behavior of each CI can be observed and analyzed through the use of domain simulators, but this does not account for their interdependency. To explore CI interdependencies, domain simulators need to be integrated in a federation where they can collaborate. This paper explores three different simulators: the EPANET water distribution simulator, the PSCAD power system simulator and the I2Sim infrastructure interdependency simulator. Each simulator's modeling approach is explored and their similarities and differences between modeling approaches are determined. Core ontology for each simulation engine is created as well as initial mapping between them. Ontologies and their mapping will support collaboration of simulators by enabling exchange of information in a semantic manner.
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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) | 0.001 | 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".