SMILE Modeling Working Group: Modeling and Analysis of X-ray and Ultraviolet Images of Solar Wind – Earth Interactions
Bibliographic record
Abstract
The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) is a joint European and Chinese spacecraft scheduled to launch in 2025 into a highly elliptical polar orbit. It will carry four instruments: the Soft X-ray Imager (SXI), the UltraViolet Imager (UVI), the Light Ion Analyzer (LIA), and the MAGnetometer (MAG). SMILE will image the dayside magnetosheath and cusps in soft X-ray, as well as the northern auroral oval in ultraviolet, for ∼41 continuous hours per orbit while simultaneously measuring plasma and magnetic field along its path. SMILE aims to advance our understanding of global solar wind - magnetosphere - ionosphere interactions. The Modeling Working Group (MWG), established in 2018, has fostered various modeling studies to ensure the successful scientific outcome of the SMILE mission. This paper overviews several MWG activities related to the SMILE SXI and UVI instruments. Firstly, we introduce the simulation of soft X-ray images of the Earth's dayside magnetosphere, the SMILE orbit, and the SXI target visibilities. Secondly, we discuss multiple techniques developed for soft X-ray image analysis and the SXI's capability to capture multi-scale interactions between the solar wind and Earth's magnetosphere. Thirdly, we focus on the role of exospheric hydrogen density in determining near-Earth soft X-ray emissions, introducing several studies that estimate the exospheric density near the subsolar magnetopause location and its variability during geomagnetic storms. Finally, we present the modeling efforts for simulating the UVI instrument performance and the kinetic transport of suprathermal electrons and their impact on UV emissions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".