Quantifying the global solar wind-magnetosphere interaction with the Solar-Terrestrial Observer for the Response of the Magnetosphere (STORM) mission concept
Bibliographic record
Abstract
Much of what we know about the solar wind’s interaction with the Earth’s magnetosphere has been gained from isolated in-situ measurements by single or multiple spacecraft. Based on their observations, we know that reconnection, whether on the dayside magnetopause or deep within the Earth’s magnetotail, controls the bulk flow of solar wind energy into and through the global system and that nightside activity provides the energized particles that power geomagnetic storms. But by their very nature these isolated in-situ measurements cannot provide an instantaneous global view of the entire system or its cross-scale dynamics. To fully quantify the dynamics of the coupled solar wind-magnetosphere requires comprehensive end-to-end global imaging of the key plasma structures that comprise the magnetosphere which have spatial resolutions that exceeds anything possible with multi-point or constellation situ measurements. Global, end-to-end, imaging provides the pathway to understanding the system as a whole, its constituent parts, and its cross-scale processes on a continuous basis, as needed to quantify the flow of solar wind energy through the global magnetospheric system. This paper describes how a comprehensively-instrumented single spacecraft in a high-altitude, high-inclination orbit coupled with ground-based instruments provides the essential observations needed to track and quantify the flow of solar wind energy through the magnetosphere. This includes observations of the solar wind plasma and magnetic field input, the magnetopause location in soft X-rays, the auroral oval in far ultraviolet, the ring current in energetic neutrals, the plasmasphere in extreme ultraviolet, the exosphere in Lyman-α, and the microstructure of the nightside auroral oval from ground-based all sky cameras.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".