How long should power system disturbance site monitoring be in order to be significant?
Bibliographic record
Abstract
The author presents the results of a statistical study on power supply disturbances monitored at a computer center over a period of two years. The results of the statistical study are discussed in detail, revealing the statistical patterns of occurrence of power supply disturbances at the site and the problematic nature of defining the duration of site monitoring. The primary objectives of the present work were: (1) to attempt to determine how long site monitoring of power system disturbances should last in order to be significant; and (2) to reveal the importance of having a sound knowledge of the possible patterns of occurrence of power supply disturbances at a selected site prior to initiating the monitoring process. It appears from the statistical analysis of the power-supply disturbances that the two-week monitoring period suggested in the IEEE Orange Book, IEEE Std. 446-1987, will provide an adequate sample provided the monitoring begins with an adequate knowledge of the site's electrical and system performance characteristics and is immediately initiated after the occurrence of two or more site disturbances.>
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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 | 0.006 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".