Bibliographic record
Abstract
In this paper some new technologies on control center issues in 2008-2009 are summarized. It includes three parts. The first part is a standard specification on next generation of EMS architecture drafted by The Working Group D2.24 of CIGRE,and five documents are to be published,including Common Requirement Document (CRD),White Paper,Standard Business Processes (SBP),Standard Business Services (SBS) and Standard Technology Services (STS),and the first two among them have been completed and published. The second part relates to Free Open Source Software (FOSS). FOSS means those types of software which can be obtained from Internet with source code free of charge,it can be used,studied,modified or distributed without any restriction,thus FOSS is very convenient for teaching and research purposes. A list of existing FOSS for power system analysis is included in this section. The third part relates to the technologies for preventing power system blackouts. In this summary experiences of two large power grids for power system restoration are presented. Practices of PJM include general principles to develop a restoration plan. The power grid configuration of Hydro-Quebec is somewhat similar to some power grids in China,their practices of developing a restoration plan is also included in this summary for interesting readers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.015 |
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".