Swarm Electric Field Instruments' Thermal Ion Imagers: A Decade of Discovery
Bibliographic record
Abstract
The Swarm mission concept is innovative in its recognition that high-quality measurements of the geomagnetic field from LEO require accurate knowledge of Earth’s plasma environment, and furthermore that combined, precision measurements of fields, plasmas and neutral density from polar orbit provide a new window into ionosphere-thermosphere-magnetosphere (ITM) coupling and science. During the first decade of operations, event-based studies have led to new discoveries such as extreme plasma flows associated with the Birkeland current systems, the electrodynamic structure of multiple auroral arcs, the sub-auroral “STEVE” phenomenon, and the existence of standing Alfvén waves at equatorial latitudes. At the same time, the mission has accumulated an extensive database of measurements at high spatial resolution collected over a wide range of condition covering nearly a full solar cycle; these data have been used in longer-term statistical studies of plasma properties, high-latitude convection and ITM coupling via Poynting flux. As we enter the next decade of operations, the Swarm data are increasingly being used to inform empirical and physics-based models of the ionosphere; these in turn will comprise an important part of the long-term legacy of the Swarm mission. This talk will highlight scientific discoveries from the first decade of EFI operations, centred on observations of ion flows and associated electric fields from the EFI’s Thermal Ion Imagers, and made possible by a large and active community of collaborators.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| 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".