An analysis of extreme-weather-related transmission line outages
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One of the primary causes of major transmission line outages are extreme weather conditions particularly lightning, wind and conductor icing (e.g., Quebec, US ice storms of 1998). The statistical results of a detailed analysis of Alberta Power Limited's transmission line outage database and Alberta Environmental Service weather databases over a 20 year period are investigated in this paper. The analysis reveals the significance of the geographical location of the transmission lines and their frequency of outages. The paper also reveals that the number of transmission line outages is not necessarily proportional to the physical length of the line for many transmission lines which contradicts may published methodologies. The paper provides the basic framework for constructing advanced probabilistic reliability models of transmission line networks (e.g., Markov models and Monte Carlo simulation models) based on the historical Canadian Electricity Association's utility equipment reliability database and the Environmental Service weather data bases.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it