The SMILE mission: A novel way to explore solar-terrestrial interactions
Bibliographic record
Abstract
The coupling between the solar wind and the Earth's magnetosphere-ionosphere system, and the geospace dynamics that result, comprise some of the key questions in space plasma physics. In situ measurements by a fleet of solar wind and magnetospheric missions, current and planned, can provide the most detailed observations of the Sun-Earth connections. However, we are still unable to quantify the global effects of the drivers of such connections, and to monitor their evolution with time. This information is the key missing link for developing a comprehensive understanding of how the Sun gives rise to and controls the Earth's plasma environment and space weather. SMILE (Solar wind Magnetosphere Ionosphere Link Explorer) is a novel self-standing mission dedicated to observing the solar wind - magnetosphere coupling via simultaneous X-ray imaging of the magnetosheath and polar cusps (large spatial scales at the magnetopause), UV imaging of global auroral distributions (mesoscale structures in the ionosphere) and in situ solar wind/magnetosheath plasma and magnetic field measurements. X-ray imaging of the magnetosheath and cusps is made possible by the X-ray emission produced in the process of solar wind charge exchange, first observed at comets, and subsequently found to occur in the vicinity of the Earth's magnetosphere. One of the science aims of SMILE is to track the substorm cycle, via X-ray imaging on the dayside and by following its consequences on the nightside with UV imaging. SMILE is a collaborative mission between ESA and the Chinese Academy of Sciences (CAS) that was selected in November 2015, adopted into ESA’s Cosmic Vision Programme in March 2019, and is due for launch at the end of 2023. The science that SMILE will deliver, as well as the ongoing technical developments and scientific preparations, and the current status of the mission, will be presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".