Bibliographic record
Abstract
On 14 August 2003, a blackout occurred in the Northeastern part of the US and in Lower Canada, causing, among other things, the normal flow of life to come to an abrupt standstill in New York City. Lots of people got stuck in elevators, the subway system halted and millions of New Yorkers came out into the streets, many of whom were forced to stay there for the night. Engineers managed to trace the origin of this blackout to Ohio: apparently, operators did not know how to deal with local disturbances and this caused several lines to get overloaded, which subsequently were switched off. The instability spread from one region to the next, resulting in the large-scale blackout (Schewe, 2007). Only a few weeks later, a major storm knocked down power lines near the Italian-Swiss border. Due to excessive loads on the remaining lines, officials decided to remove Italy from the European grid. Less than two minutes after this decision’s implementation, frequency instabilities caused a complete collapse of the Italian electricity system, virtually throwing Italy into darkness. In Rome, where the annual Notte Bianca festival was taking place, the power outage created chaos after the subway system stopped functioning, leaving thousands of festival visitors stranded. The death of at least four people was directly attributed to the power outage (Lagendijk, 2008).
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".