Quantitative maps of geomagnetic perturbation vectors during substorm onset and recovery
Bibliographic record
Abstract
Abstract We have produced the first series of spherical harmonic, numerical maps of the time‐dependent surface perturbations in the Earth's magnetic field following the onset of substorms. Data from 124 ground magnetometer stations in the Northern Hemisphere at geomagnetic latitudes above 33° were used. Ground station data averaged over 5 min intervals covering 8 years (1998–2005) were used to construct pseudo auroral upper, auroral lower, and auroral electrojet (AU*, AL*, and AE*) indices. These indices were used to generate a list of substorms that extended from 1998 to 2005, through a combination of automated processing and visual checks. Events were sorted by interplanetary magnetic field (IMF) orientation (at the Advanced Composition Explorer (ACE) satellite), dipole tilt angle, and substorm magnitude. Within each category, the events were aligned on substorm onset. A spherical cap harmonic analysis was used to obtain a least error fit of the substorm disturbance patterns at 5 min intervals up to 90 min after onset. The fits obtained at onset time were subtracted from all subsequent fits, for each group of substorm events. Maps of the three vector components of the averaged magnetic perturbations were constructed to show the effects of substorm currents. These maps are produced for several specific ranges of values for the peak |AL*| index, IMF orientation, and dipole tilt angle. We demonstrate an influence of the dipole tilt angle on the response to substorms. Our results indicate that there are downward currents poleward and upward currents just equatorward of the peak in the substorms' westward electrojet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".