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Record W1979127544 · doi:10.1002/2014eo480001

Magnetic Storms and Induction Hazards

2014· article· en· W1979127544 on OpenAlexaboutno aff
Jeffrey J. Love, E. J. Rigler, A. Pulkkinen, C. C. Balch

Bibliographic record

VenueEos · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationU.S. Geological SurveyNational Aeronautics and Space Administration
KeywordsGeomagnetic stormStormElectromagnetic inductionElectricityEarth's magnetic fieldMagnetic fieldCivilizationGeophysicsGridMeteorologyElectrical engineeringEngineeringEnvironmental sciencePhysicsGeologyHistoryGeodesyArchaeology

Abstract

fetched live from OpenAlex

Magnetic storms are potentially hazardous to the activities and technological infrastructure of modern civilization. This reality was dramatically demonstrated during the great magnetic storm of March 1989, when surface geoelectric fields, produced by the interaction of the time‐varying geomagnetic field with the Earth's electrically conducting interior, coupled onto the overlying Hydro‐Québec electric power grid in Canada. Protective relays were tripped, the grid collapsed, and about 9 million people were temporarily left without electricity [Bolduc, 2002].

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.006
GPT teacher head0.177
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations30
Published2014
Admission routes1
Has abstractyes

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