Investigation of Plasma Composition and Small-Scale Density Irregularities on a Non-circular and Non-Sun-Synchronous Polar Low-Earth-Orbit (LEO) Satellite: Swarm-E e-POP Observations in the F-region and Topside Ionosphere-Thermosphere
Bibliographic record
Abstract
The Swarm-E/Enhanced Polar Outflow Probe (e-POP) is in an elliptic (non-circular) and non-Sun-synchronous polar orbit (81° inclination, 325 km perigee × 1500 km initial apogee). This gives the satellite a unique vantage point among LEO satellites for observing plasma and related space weather processes in the topside ionosphere and thermosphere, especially the altitude variations of specific physical phenomena. The imaging and rapid-scanning ion mass spectrometer (IRM) on Swarm E combines the technique of ion time-of-flight (TOF), hemispherical electrostatic analysis, and 2D positional ion detection (imaging) to resolve the mass-per-charge (M/q), energy-per-charge (E/q), and incident direction of each detected ion, and to simultaneously measure the incident plasma current at high (1-ms) cadence. Data acquired over the 8-year period from launch (September 2013) to December 2021 has enabled the quantitative investigation of several important magnetosphere-ionosphere-thermosphere (MIT) coupling processes and the altitude distributions and variations of the resulting plasma composition, structure, and dynamics in the F-region and topside ionosphere-thermosphere. These include the effects of atmospheric photoelectrons on spacecraft charging, molecular and nitrogen (N+) ion enhancements in the active-time auroral ionosphere, and decameter-scale structures in equatorial plasma bubbles, for example. We present an overview of investigations of the long- (solar-cycle time scale) and short-term (down to substorm time scale) variations of the various observed features and associated phenomena in the context of their impact on MIT coupling.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".