Ten Years of Low-Earth Orbit Observations from CASSIOPE/Swarm-Echo
Bibliographic record
Abstract
From the vantage point of an elliptic, polar, low-earth orbit (81o inclination, 325 km x 1500 km initial apogee/perigee), CASSIOPE/Swarm-Echo has been observing the ionosphere-thermosphere system for over ten years. The Enhanced Polar Outflow Probe (e-POP) payload onboard collects data on space weather and related phenomena, including measurements of the local magnetic field, low-energy ion and electron energy distributions, high-frequency radio waves (natural and man-made), GPS signals, and aurora. These observations from a non-sun-synchronous orbit over a range of altitudes constitutes a unique data set that allows for investigation of the earth’s magnetic field and related current systems, upper atmospheric dynamics, auroral dynamics, and related coupling processes among the magnetosphere, ionosphere, thermosphere, and plasmasphere. This presentation will highlight the discoveries of the ten years of e-POP operation, including recent work on plasma waves generated by moving charged space objects and machine-learning techniques applied to analysis of magnetic field data and auroral images. We will also present some of the new Swarm-Echo data products and system tools available for use and look at the future direction of both the mission and the evolving data set.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".