GPS phase scintillation at high latitudes during geomagnetic storms of 7–17 March 2012 – Part 2: Interhemispheric comparison
Bibliographic record
Abstract
Abstract. During the ascending phase of solar cycle 24, a series of interplanetary coronal mass ejections (ICMEs) in the period 7–17 March 2012 caused geomagnetic storms that strongly affected high-latitude ionosphere in the Northern and Southern Hemisphere. GPS phase scintillation was observed at northern and southern high latitudes by arrays of GPS ionospheric scintillation and TEC monitors (GISTMs) and geodetic-quality GPS receivers sampling at 1 Hz. Mapped as a function of magnetic latitude and magnetic local time (MLT), the scintillation was observed in the ionospheric cusp, the tongue of ionization fragmented into patches, sun-aligned arcs in the polar cap, and nightside auroral oval and subauroral latitudes. Complementing a companion paper (Prikryl et al., 2015a) that focuses on the high-latitude ionospheric response to variable solar wind in the North American sector, interhemispheric comparison reveals commonalities as well as differences and asymmetries between the northern and southern high latitudes, as a consequence of the coupling between the solar wind and magnetosphere. The interhemispheric asymmetries are caused by the dawn–dusk component of the interplanetary magnetic field controlling the MLT of the cusp entry of the storm-enhanced density plasma into the polar cap and the orientation relative to the noon–midnight meridian of the tongue of ionization.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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".