Premidnight Preponderance of Dispersionless Ion and Electron Injections
Bibliographic record
Abstract
Energetic particle injections, observed as sudden particle flux enhancements at energies of tens to hundreds keV, are signatures of particle transport and energization. They are significant in supplying inner magnetosphere seed populations, and are important for understanding magnetotail energization and transport processes. Therefore, studying plasma and field measurements as well as ephemeris data simultaneous to injections can help elucidate the physics behind particle transport and energization necessary for understanding and modeling the magnetosphere. Until recently, injections were considered to occur most frequently around midnight. However, Time History of Events and Macroscale Interactions During Substorms (THEMIS) satellites, have observed that both dispersionless ion and electron injections are prevalent in the premidnight sector. A retrospective review of studies from geosynchronous orbit out to ~35 RE also reveals such a dawn-dusk asymmetry in injection occurrence rates. The premidnight preponderance of injections provides evidence of a relationship between injections and other phenomena having a similar dawn-dusk asymmetry, such as fast flows, dipolarizing flux bundles, and reconnection. A superposed epoch analysis of these phenomena further illustrates these relationships. This chapter reviews injection studies relevant to dawn-dusk asymmetries in the magnetosphere, and therefore focuses on literature that has explored where injections occur throughout the magnetotail.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".