Dynamics of Electron Flux in the Slot Region and Geomagnetic Activity
Bibliographic record
Abstract
Abstract The slot region between the radiation belts in the magnetosphere is statistically less populated by the energetic electrons, which makes it attractive in the design considerations of the satellite missions. As has been shown in the last decades, the dynamics of this region is complicated, with strong enhancements of electron density associated with space weather events. This paper provides an analysis of the dynamics of electron flux in 1998–2007 with specific attention to slot filling events and preceding geomagnetic activity. Flux of energetic electrons, with energies E > 0.63 MeV, E > 1.5 MeV, and E > 3 MeV, was obtained from detectors on board the HEO‐3 satellite in highly elliptical orbit. To evaluate geomagnetic conditions, associated with enhancement of electron flux, all the “slot filling events” were studied together with geomagnetic activity provided by Dst and Kp global indices as well as with the hourly range indices of geomagnetic variations at mid‐latitude. These geomagnetic indices were used for assessment of a threshold and frequency of occurrence of slot filling events. Regression analysis has been used to find a relationship between the maximum filling of the slot region due to space weather event and the preceding geomagnetic activity level. Influence of the cumulative time of periods of enhanced geomagnetic activity to the variation of the electron flux in the slot region has been analyzed. Suitability of different indices of geomagnetic activity for estimation of the rate of occurrence of slot filling events and for assessment of electron flux in the slot region is discussed.
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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 | 0.000 |
| 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".