Longitudinal Development of Cosmic Noise Absorption Based on Multipoint Observations at Subauroral Latitudes During Storm‐Time Substorms on 25–28 August 2018
Bibliographic record
Abstract
Abstract Enhancements in electron density in the D‐region ionosphere attributed to the precipitation of high‐energy electrons, have previously been inferred from increases in cosmic radio noise absorption (CNA) using ground‐based riometers. However, there have been few studies of CNA observations at multi‐point stations distributed in longitudes. Thus, the spatio‐temporal development of the global distribution of CNA is not well understood. In this study, we investigated the longitudinal extent of CNA using simultaneous riometer observations at six stations at subauroral latitudes in Canada, Alaska, Russia, and Iceland. These stations are located encircling the earth at ∼60° north magnetic latitudes. We have conducted simultaneous observations of CNA at these stations since October 2017. Here we focus on seven substorms during a geomagnetic storm 25–28 August 2018 and study the spatio‐temporal development of the global distribution of CNA during these substorms. For all seven substorms, some stations observed CNA enhancements after the substorm onsets. In five cases, the CNA enhancements started around midnight and expanded eastward. The other two cases show westward and anti‐sunward development of CNA. The eastward expansion of CNA indicates the eastward drift of high‐energy electrons, which is the source of the CNA, due to gradient and curvature drift in the geomagnetic field. The westward expansion of CNA may correspond to westward expansion of the substorm injection region due to dawn‐to‐dusk electric fields. These results indicate that spatio‐temporal development of CNA at subauroral latitudes corresponds to high energy electron drift in the inner magnetosphere.
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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) | 0.001 | 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".