MétaCan
Menu
Back to cohort
Record W2765877021 · doi:10.1002/2017sw001695

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross‐Polar Cap Potential

2017· article· en· W2765877021 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

VenueSpace Weather · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersLos Alamos National LaboratoryCollege of Pharmacy, University of MichiganGoddard Space Flight CenterNational Oceanic and Atmospheric AdministrationAlberta Agricultural Research InstituteUniversità degli Studi dell'AquilaLaboratory Directed Research and DevelopmentU.S. Geological SurveyU.S. Department of EnergyEuropean CommissionFlorida Institute of TechnologyUniversity of MichiganNational Aeronautics and Space Administration
KeywordsMagnetospherePolarGeomagnetic stormMean squared errorEarth's magnetic fieldPhysicsSolar windMeteorologyAtmospheric sciencesEnvironmental scienceMathematicsStatisticsAstronomyMagnetic field

Abstract

fetched live from OpenAlex

Abstract We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model and tested two different grid resolutions. We evaluated the model's accuracy in predicting K p , S Y M ‐ H , A L , and cross‐polar cap potential (CPCP). We find that the model does an excellent job of predicting the S Y M ‐ H index, with a root‐mean‐square error (RMSE) of 17–18 nT. K p is predicted well during storm time conditions but overpredicted during quiet times by a margin of 1 to 1.7 K p units. A L is predicted reasonably well on average, with an RMSE of 230–270 nT. However, the model reaches the largest negative A L values significantly less often than the observations. The model tended to overpredict CPCP, with RMSE values on the order of 46–48 kV. We found the results to be insensitive to grid resolution, with the exception of the rate of occurrence for strongly negative A L values. The use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.995

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)0.0060.000

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 head0.004
GPT teacher head0.245
Teacher spread0.241 · 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