Bibliographic record
Abstract
Recent events have shown that natural and human made disasters, acts of terrorism and massive technological failures can have a profound impact on the safety and security of people and critical infrastructure. Given the scope of existing codes and standards, the development work sponsored by the ASCE/AEI, "Recommended Practices for Control, Communication and Power (C2P) of Critical Facilities", to identify ways to improve the resistance of critical electrical infrastructure to disaster, is essential. These recommended practices are intended to augment and not replace engineering requirements promulgated or enforced by the regulatory bodies and authorities having jurisdiction. This work presents a compelling opportunity to embrace a harmonized solution — a single document that will draw on the experiences and lessons of the standards community throughout North America to address issues that are mutually imperative. A harmonized approach is preferred over a national one for several reasons, as this paper will explore. The interests of manufacturers, regulators, specifiers, and users will best be served if Canadian and U.S. representatives undertake the C2P work jointly, with a harmonized document as its outcome. The experience of the standards community in harmonization efforts provides important insights that may be applied to a harmonized C2P process.
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 | 0.033 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".