RISE: REST-ing heterogeneous simulations interoperability
Bibliographic record
Abstract
Interoperating heterogeneous simulation models and tools is becoming a necessity in today's cross-enterprise collaboration market. Nevertheless, simulation models and engines have evolved apart in many directions, making their interoperability extremely complex. We present the RESTful Interoperability Simulation Environment (RISE), which provides the means for interoperating simulation heterogeneous assets. RISE uses Service-Oriented RESTful web-services, and it is based on three aspects: the framework architecture, the modeling level and the simulation synchronization level. RISE is independent of any simulation engine, theory or an algorithm. However, it provides different rules for simulation domains with conservative or optimistic synchronization algorithms. Further, RISE does not require any implementation changes related to domain modeling or simulation methods. Furthermore, it hides domain internal specifics, giving freedom to define different internal implementation and algorithms. The presented work here is part of the on-going effort in the DEVS community to interoperate different DEVS-based simulation assets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".