Assessment of extreme values in geomagnetic and geoelectric field variations for Canada
Bibliographic record
Abstract
Abstract Disturbances of the geomagnetic field produced by space weather events can have an impact on power systems and other critical infrastructure. To mitigate these risks it is important to determine the extreme values of geomagnetic activity that can occur. More than 40 years of 1 min magnetic data recorded at 13 Canadian geomagnetic observatories have been analyzed to evaluate extreme levels in geomagnetic and geoelectric activities in different locations of Canada. The hourly ranges of geomagnetic field variations and hourly maximum in rate of change of the magnetic variations have been used as measures of geomagnetic activity. Geoelectric activity is estimated by the hourly peak amplitude of the geoelectric fields calculated with the use of Earth resistivity models specified for different locations in Canada. A generalized extreme value distribution was applied to geomagnetic and geoelectric indices to evaluate extreme geomagnetic and geoelectric disturbances, which could happen once per 50 and once per 100 years with 99% confidence interval. Influence of geomagnetic latitude and Earth resistivity models on the results for the extreme geomagnetic and geoelectric activity is discussed. The extreme values provide criteria for assessing the vulnerability of power systems and other technology to geomagnetic activity for design or mitigation purposes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".