SOFTWARE IMPLEMENTATION OF CONTROLLER REPRESENTATION IN THE OVNI SIMULATOR
Bibliographic record
Abstract
Abstract – This paper presents the latest advancements in the development of OVNI (Object Virtual Network Integrator) power system simulator regarding the imple-mentation of controllers. OVNI’s object oriented descrip-tion of the power network and its exploitation of the coarse grain parallelization granularity provided by the Multi-Area Thévénin Equivalent (MATE) concept, offers great generality, flexibility and efficiency for implementation in software of controllers. Controller elements (i.e. transfer functions, limiters etc.) are objects of the controller ele-ment class, and they interact with each other through a controller element interface. As controller elements are completely encapsulated within their class definition, and their communication interface is clearly defined, the pre-sented approach provides great flexibility in adding new controller elements and controllers to OVNI. A general user interface offers capabilities of custom designing con-trollers and/or use of predefined ones already available in OVNI.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".