Quantitative Evaluation of Radial Diffusion and Local Acceleration Processes During GEM Challenge Events
Bibliographic record
Abstract
Abstract We simulate the radiation belt electron flux enhancements during selected Geospace Environment Modeling (GEM) challenge events to quantitatively compare the major processes involved in relativistic electron acceleration under different conditions. Van Allen Probes observed significant electron flux enhancement during both the storm time of 17–18 March 2013 and non–storm time of 19–20 September 2013, but the distributions of plasma waves and energetic electrons for the two events were dramatically different. During 17–18 March 2013, the SYM ‐ H minimum reached −130 nT, intense chorus waves (peak B w ~140 pT) occurred at 3.5 < L < 5.5, and several hundred keV to several MeV electron fluxes increased by ~2 orders of magnitude mostly at 3.5 < L < 5.5. During 19–20 September 2013, the SYM ‐ H remained higher than −30 nT, modestly intense chorus waves (peak B w ~80 pT) occurred at L > 5.5, and electron fluxes at energies up to 3 MeV increased by a factor of ~5 at L > 5.5. The two electron flux enhancement events were simulated using the available wave distribution and diffusion coefficients from the GEM focus group Quantitative Assessment of Radiation Belt Modeling. By comparing the individual roles of local electron heating and radial transport, our simulation indicates that resonant interaction with chorus waves is the dominant process that accounts for the electron flux enhancement during the storm time event particularly near the flux peak locations, while radial diffusion by ultralow‐frequency waves plays a dominant role in the enhancement during the non–storm time event. Incorporation of both processes reasonably reproduces the observed location and magnitude of electron flux enhancement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".