Utilizing the Heliophysics/Geospace System Observatory to Understand Particle Injections: Their Scale Sizes and Propagation Directions
Bibliographic record
Abstract
Abstract The injection region's formation, scale size, and propagation direction have been debated throughout the years, with new questions arising with increased plasma sheet observations by missions like Cluster and THEMIS. How do temporally and spatially small‐scale injections relate to the larger injections historically observed at geosynchronous orbit? How to account for opposing propagation directions—earthward, tailward, and azimuthal—observed by different studies? To address these questions, we used a combination of multisatellite and ground‐based observations to knit together a cohesive story explaining injection formation, propagation, and differing spatial scales and timescales. We used a case study to put statistics into context. First, fast earthward flows with embedded small‐scale dipolarizing flux bundles transport both magnetic flux and energetic particles earthward, resulting in minutes‐long injection signatures. Next, a large‐scale injection propagates azimuthally and poleward/tailward, observed in situ as enhanced flux and on the ground in the riometer signal. The large‐scale dipolarization propagates in a similar direction and speed as the large‐scale electron injection. We suggest small‐scale injections result from earthward‐propagating, small‐scale dipolarizing flux bundles, which rapidly contribute to the large‐scale dipolarization. We suggest the large‐scale dipolarization is the source of the large‐scale electron injection region, such that as dipolarization expands, so does the injection. The >90‐keV ion flux increased and decreased with the plasma flow, which died at the satellites as global dipolarization engulfed them. We suggest the ion injection region at these energies in the plasma sheet is better organized by the plasma flow.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".