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Record W4390122324 · doi:10.1016/j.softx.2023.101619

Global-GMDs: The global map of geomagnetic disturbances

2023· article· en· W4390122324 on OpenAlexfundno aff
Hongyi Hu, Zhonghua Xu

Bibliographic record

VenueSoftwareX · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersCommission Géologique du CanadaBritish Antarctic SurveyUniversità degli Studi dell'AquilaSveriges Geologiska UndersökningFlorida Institute of TechnologyAlberta Agricultural Research InstituteHelmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZUniversitetet i TromsøNational Aeronautics and Space Administration
KeywordsEarth's magnetic fieldGridKrigingGeomagnetic stormSoftwareComputer scienceField (mathematics)GeophysicsRemote sensingGeologyEnvironmental scienceGeodesyMagnetic fieldMathematicsPhysics

Abstract

fetched live from OpenAlex

To improve the understanding and monitoring the impacts of geomagnetic disturbances (GMDs) on power grids globally, the presented software, Global-GMDs, uses magnetic field measurements from geomagnetic observatories worldwide and Kriging method to generate global maps of GMDs. It provides better observational information during a solar storm to power grid operations and other crucial infrastructures. It can also help researchers to assess the GMDs prediction model by comparing with Global-GMDs maps and to get better understanding of physics mechanisms.

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)0.001
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: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.008

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 head0.005
GPT teacher head0.232
Teacher spread0.226 · 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
GenreSoftware

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

Citations1
Published2023
Admission routes1
Has abstractyes

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