Formation and Motion of Horse Collar Aurora Events
Bibliographic record
Abstract
Abstract The polar cap can become teardrop shaped through the poleward expansion of the dusk and dawn sectors of the auroral oval, to form what is called horse collar aurora (HCA). The formation of HCA has been linked to dual‐lobe reconnection (DLR) where magnetic flux is closed at the dayside magnetopause. A prolonged period of northward IMF is required for the formation of HCA. HCA have previously been identified in UV images captured by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) instrument on‐board the Defense Meteorological Satellite Program (DMSP) spacecraft F16, F17 and F18. Events that have concurrent 630.0 nm all‐sky camera (ASC) data from the Redline Geospace Observatory (REGO) Resolute Bay site are now studied in more detail, making use of the higher cadence of the ASC images compared to DMSP/SSUSI. 11 HCA events are studied and classified based on the IMF conditions at the end of the event. Five of the events were found to end via a southward turning of the IMF, two end with positive B y dominated IMF and four with negative B y dominance. Under positive (negative) B y the arcs move duskward (dawnward) in the northern hemisphere with the opposite true in the southern hemisphere. Under a southward turning the arcs move equatorward. One event is of particular interest as it occurred while there was a transpolar arc (TPA) also present. Understanding the evolution of HCA will allow DLR to be studied in more detail.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".