Visualization of ion cyclotron wave and particle interactions in the inner magnetosphere via THEMIS‐ASI observations
Bibliographic record
Abstract
Interaction with EMIC (electromagnetic ion cyclotron) waves is thought to be a key component contributing to the very rapid loss of both ring current and radiation belt particles into the atmosphere. Estimated loss rates are heavily dependent on the assumed spatial distribution of the EMIC wave. Statistical maps of the spatial distribution have been produced using in‐situ satellite data. However, with limited satellite data it is impossible to deduce the true spatial distribution. In this study, we present ground‐based observations using all‐sky imager and search coil magnetometer networks, which provide the large‐scale distribution and motion of the EMIC wave‐particle interaction regions. We observed several spots of isolated proton auroras simultaneously with Pc1/EMIC waves at subauroral latitudes during the expansion phase of a storm‐time substorm on 9 March 2008. The isolated auroras were distributed over ∼4‐hours MLT preceding midnight. The POES‐17 satellite confirmed enhancements of 30‐keV proton precipitations over the isolated auroras. The equatorward motion of the auroras and frequency drift of the wave were consistent with the plasmasphere eroding due to a polar cap potential enhancement modeled by a numerical simulation. We also found that relativistic electron precipitation was not always associated with the isolated aurora, depending strongly on the plasma density profile near the plasmapause. This study shows that the specific distribution of ring current proton precipitation can be visualized through the ground network observations. By combining with upcoming inner‐magnetosphere satellite missions, these remote‐sensing observations are very important for quantitative understanding of the particle loss in the inner magnetosphere.
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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".