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Record W1969641913 · doi:10.1109/emceco.2007.4371705

Real-Time Simulation of Geomagnetically Induced Currents

2007· article· en· W1969641913 on OpenAlexaff
D. H. Boteler, L. Trichtchenko, Risto Pirjola, J. A. Parmelee, S. Souksaly, Aidan Foss, L. Marti

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsHydro One (Canada)Natural Resources Canada
Fundersnot available
KeywordsGeomagnetically induced currentEarth's magnetic fieldElectric power systemElectric power transmissionMagnetic fieldElectric fieldPower (physics)GeophysicsGeomagnetic stormMeteorologyComputer scienceGeologyElectrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

To monitor the impact of geomagnetic disturbances on a power network a system has been developed to provide real-time simulations of the geomagnetically induced currents flowing in a power system. The Real- Time GIC Simulator uses real-time magnetic data from a magnetic observatory. This is combined with a model of the earth conductivity structure to determine the electric field produced by the magnetic field variations. This electric field becomes the input to a model of the power system which calculates the GIC in the transmission lines and flowing to/from ground at the substations. These model results are displayed in a set of graphs and tables that can provide engineers and system operators with a continually updating view of the magnitudes of GIC in the network.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.265
Teacher spread0.256 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations19
Published2007
Admission routes1
Has abstractyes

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