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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 OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.854

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 head0.005
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