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Record W2166280084 · doi:10.1002/ggge.20242

A magnetic disturbance index for Mercury's magnetic field derived from MESSENGER Magnetometer data

2013· article· en· W2166280084 on OpenAlexafffund
B. J. Anderson, C. L. Johnson, H. Korth

Bibliographic record

VenueGeochemistry Geophysics Geosystems · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCarnegie Institution of WashingtonJohns Hopkins UniversityNational Aeronautics and Space Administration
KeywordsMagnetometerMagnetosphereDisturbance (geology)LatitudeMagnetic fieldGeophysicsGeologyMagnetic anomalyMagnetopauseGeodesyAtmospheric sciencesPhysicsGeomorphology

Abstract

fetched live from OpenAlex

We present a magnetic disturbance measure for Mercury derived from MESSENGER Magnetometer data. Magnetic field fluctuations were computed in three period bands: 0.1–2 s, 2–20 s, and 20–300 s. From these, we determined log average magnetic variability versus latitude and local time in Mercury's magnetosphere. The quietest regions are the southern tail lobe and the nightside poleward of 30° magnetic latitude, and the most disturbed regions are near magnetopause boundaries and the magnetospheric cusp. We used ratios at each location between the mean disturbance and that observed on each pass to compute normalized measures of magnetic disturbance for each orbit. Composite disturbance indices incorporate disturbance levels in all three bands. Percentile ranking of the composite indices provides a quantitative basis for selecting data from quiet to disturbed conditions.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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 designSimulation or modeling
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

Citations48
Published2013
Admission routes2
Has abstractyes

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