Precipitation of relativistic electrons of the Van Allen belts into the proton aurora
Bibliographic record
Abstract
The Van Allen electron belts consist of two regions encircling the earth in which relativistic electrons are trapped in the earth's magnetic field. Populations of relativistic electrons in the Van Allen belts vary greatly with geomagnetic disturbance and they are a major source of damage to space vehicles. In order to know when and by how much these populations of relativistic electrons increase, it is important to elucidate not only the cause of acceleration of relativistic electrons but also the cause of their loss from the Van Allen belts. Here we show the first evidence that left-hand polarized electromagnetic ion cyclotron (EMIC) plasma waves can cause the loss of relativistic electrons into the atmosphere, on the basis of results of an excellent set of ground and satellite observations showing coincident precipitation of ions with energies of tens of keV and of relativistic electrons into an isolated proton aurora. The proton aurora was produced by precipitation of ions with energies of tens of keV due to EMIC waves near the plasma pause, which is a manifestation of wave-particle interactions. These observations clarify that ions with energies of tens of keV affect the evolution of relativistic electrons in the Van Allen belts via parasitic resonance with EMIC waves, an effect that was first theoretically predicted in the early 1970's.
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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 | 0.000 | 0.000 |
| 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".