NERC's Reliability Assurance Initiative: What Registered Entities Can Do
Bibliographic record
Abstract
Abstract In the summer of 2003, a handful of power lines in Ohio tripped after making contact with overgrown trees. Over the next 13 minutes, the electric grid experienced cascading failures that left an estimated 50 million people in the United States and Canada without power. Two years later, Congress added Section 215 to the Federal Power Act, giving the Federal Energy Regulatory Commission (FERC) jurisdiction over the reliability of the bulk power system (BPS). Section 215 also directed FERC to designate an Electric Reliability Organization (ERO) to establish and enforce reliability standards with penalties up to a million dollars per day per violation.
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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 | 0.048 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.059 | 0.027 |
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".