New Magnetospheric Substorm Injection Monitor: Image Electron Spectrometer On Board a Chinese Navigation IGSO Satellite
Bibliographic record
Abstract
Abstract Substorm injections are one of the most dynamic processes in Earth's magnetosphere and have global consequences and broad implications for space weather modeling. They can be monitored using energetic electron detectors on geosynchronous satellites. The Imaging Electron Spectrometer (IES) on board a Chinese navigation satellite, launched on 16 October 2015 into an inclined geosynchronous satellite orbit (IGSO), provides the first energetic electron measurement in IGSO orbit to the best of our knowledge. The IES was developed by Peking University and is named hereafter as BD‐IES. Using a pin‐hole technique, the BD‐IES instrument measures 50–600 keV incident electrons in eight energy channels from nine directions covering a range of 180° in polar angle. Data collection by the BD‐IES instrument have recently passed the 1 year mark, which reflects a successful milestone for the mission. The innermost and outermost signatures of substorm injection at L ~ 6 and 12 have been observed by the BD‐IES with a high L shell spatial coverage, complementary to the existing missions such as the Van Allen Probes that covers the range below L ~ 6. There are another two BD‐IES instruments to be installed in the coming Chinese Sun‐synchronous and geosynchronous satellites, respectively. Such a configuration will provide a unique opportunity to investigate inward and outward radial propagation of the substorm injection region simultaneously at high and low L shells. It will further elucidate potential mechanisms for the particle energization and transport, two of the most important topics in magnetospheric dynamics.
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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".