Identifying STEVE's Magnetospheric Driver Using Conjugate Observations in the Magnetosphere and on the Ground
Bibliographic record
Abstract
Abstract The magnetospheric driver of strong thermal emission velocity enhancement (STEVE) is investigated using conjugate observations when Van Allen Probes' footprint directly crossed both STEVE and stable red aurora (SAR) arc. In the ionosphere, STEVE is associated with subauroral ion drift features, including electron temperature peak, density gradient, and westward ion flow. The SAR arc at lower latitudes corresponds to regions inside the plasmapause with isotropic plasma heating, which causes redline‐only SAR emission via heat conduction. STEVE corresponds to the sharp plasmapause boundary containing quasi‐static subauroral ion drift electric field and parallel‐accelerated electrons by kinetic Alfvén waves. These parallel electrons could precipitate and be accelerated via auroral acceleration processes powered by Alfvén waves propagating along the magnetic field with the plasmapause as a waveguide. The electron precipitation, superimposed on the heat conduction, could explain multiwavelength continuous STEVE emission. The green picket‐fence emissions are likely optical manifestations of electron precipitation associated with wave structures traveling along the plasmapause.
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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".