Inverse electron energy dispersion from moving auroral forms
Bibliographic record
Abstract
Abstract Numerous published examples of energy‐dispersed bursts show electron energies reaching as high as several keV and decaying to lower energies over a fraction of 1 s. This signature has been interpreted by some authors as due to impulsive acceleration to a broad range of energies in a localized region and by others as the result of impulsive, dispersive Alfvén waves, in which case the acceleration takes place over an extended distance along magnetic field lines. A survey by the Suprathermal (0–350 eV) Electron Imager on the Enhanced Polar Outflow Probe (ePOP) in the topside ionosphere has produced examples of high‐to‐low (“regular”) energy dispersion, but also a smaller number of examples exhibiting low‐to‐high (“inverse”) dispersion, which to our knowledge has not been reported before. Motivated by a recent report of regular electron dispersion produced by auroral rays moving faster than the E × B drift speed, we investigate a heuristic model of electron acceleration within a region of uniform electric field parallel to B which extends a distance La along magnetic field lines. We show that in addition to a broad range of energies, this model produces inverse dispersion when the detector is less than La beneath the bottom of the acceleration region and regular dispersion for detector distances larger than La. This simple model is meant to inform future efforts to construct a more physical model of suprathermal electron acceleration within moving auroral forms and suggests that inverse dispersion indicates relative proximity to an altitude‐extended acceleration region.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".