RCM‐E and AMIE studies of the Harang reversal formation during a steady magnetospheric convection event
Bibliographic record
Abstract
Abstract This paper presents the results of a modeling study on the formation of the Harang reversal (HR) during a steady magnetospheric convection event. The Harang reversal is identified as the boundary of the northward and southward electric field in the nightside auroral zone using the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure. We simulate the event with the Rice Convection Model‐Equilibrium (RCM‐E) by adjusting its boundary conditions to approximately match Time History of Events and Macroscale Interactions during Substorms (THEMIS) and GOES observations in the nightside magnetosphere. Our results show that the HR is collocated with an upward region 1 field‐aligned current, where converging ionospheric currents cause a southward/northward electric field on the poleward/equatorward side of the HR. Our results also indicate that the electric field reversal is slightly poleward of the ionospheric east–west current reversal and is to the northeast of the ground magnetic reversal, which is consistent with previous observations. We also test the sensitivity of the HR formation to a variety of parameters in the RCM‐E simulations. We find that (1) the reduction of the flux tube entropy parameter PV 5/3 near the midnight sector plays a major role in the formation of the HR; (2) a run carried out assuming uniform conductance produced the same major features as the run with more realistic precipitation‐enhanced conductance; and (3) the detailed pattern of the polar cap potential distribution plays a minor role, but its dawn‐dusk asymmetry significantly controls the location of the HR with respect to midnight. The RCM‐E simulations also predict PV 5/3 and flow distributions associated with the magnetospheric source of the HR in the plasma sheet, which can be further tested against observations.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".