Auroral fragmentation into patches
Bibliographic record
Abstract
Abstract Auroral patches in diffuse auroras are very common features in the postmidnight local time. However, the processes that produce auroral patches are not yet well understood. In this paper we present two examples of auroral fragmentation which is the process by which uniform aurora is broken into several fragments to form auroral patches. These examples were observed at Athabasca, Canada (geomagnetic latitude: 61.7°N), and Tromsø, Norway (67.1°N). Captured in sequences of images, the auroral fragmentation occurs as finger‐like structures developing latitudinally with horizontal‐scale sizes of 40–100 km at ionospheric altitudes. The structures tend to develop in a north‐south direction with speeds of 150–420 m/s without any shearing motion, suggesting that pressure‐driven instability in the balance between the earthward magnetic‐tension force and the tailward pressure gradient force in the magnetosphere is the main driving force of the auroral fragmentation. Therefore, these observations indicate that auroral fragmentation associated with pressure‐driven instability is a process that creates auroral patches. The observed slow eastward drift of aurora during the auroral fragmentation suggests that fragmentation occurs in low‐energy ambient plasma.
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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 | 0.001 |
| 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) | 0.004 | 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".