Security Guideline for the Electricity Sector: Threat and Incident Reporting
Bibliographic record
Abstract
It is in the public interest for NERC to develop guidelines that are useful for improving the reliability of the bulk power system. Guidelines provide suggested guidance on a particular topic for use by bulk power system entities according to each entity’s facts and circumstances and not to provide binding norms, establish mandatory reliability standards, or be used to monitor or enforce compliance. Purpose: The criteria described in this guideline are intended to assist entities to identify and classify incidents for reporting to the Electricity Sector Information Sharing and Analysis Center (ES-ISAC). These criteria include, but are not limited to, reporting requirements imposed by some NERC standards (e.g., CIP-001, CIP-008, and EOP-004) and the U.S. Department of Energy (DOE) (OE-417) and requests for voluntary reporting from the U.S. Department of Homeland Security (DHS) and Public Safety Canada/Royal Canadian Mounted Police (RCMP) (a cross-reference is included as Appendix A). This guideline also identifies available reporting mechanisms. Operated by NERC, the ES-ISAC serves the electricity sector by facilitating communications between electricity sector entities, U.S. and Canadian federal governments, and other critical infrastructure sectors. The ES-ISAC promptly disseminates threat indications, analyses and warnings to assist electricity sector entities to evaluate the situation and take appropriate actions. Scope of Application: This guideline focuses on incidents that have adversely affected or have the potential to adversely affect the reliability of the bulk power system. It is intended for use by owners, operators, and users of the bulk power system. The criteria in this guideline are not requirements, nor should they be construed as such. This guideline does not supersede reporting required for power system operation or as required by law. Version 2.0
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 | 0.032 | 0.087 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.019 | 0.009 |
| Insufficient payload (model declined to judge) | 0.019 | 0.030 |
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".