The CASSIOPE/e-POP Magnetic Field Instrument (MGF)
Bibliographic record
Abstract
Field-aligned currents couple energy between the Earth’s magnetosphere and ionosphere and are responsible for driving both micro and macro motions of plasma and neutral atoms in both regimes. These currents are believed to be a contributing energy source for ion acceleration in the polar ionosphere and may be detected via measurements of magnetic gradients along the track of a polar orbiting spacecraft, usually the north-south gradients of the east-west field component. The detection of such gradients does not require observatory class measurements of the geomagnetic field. The Magnetic Field instrument (MGF) measures the local magnetic field onboard the Enhanced Polar Outflow Probe (e-POP) satellite by using two ring-core fluxgate sensors to characterize and remove the stray spacecraft field. The fluxgate sensors have their heritage in the MAGSAT design, are double wound for reduced mass and cross-field dependence, and are mounted on a modest 0.9 m carbon-fiber boom. The MGF samples the magnetic field 160 times per sec (∼50 meters) to a resolution of 0.0625 nT and outputs data at 1952 bytes per second including temperature measurements. Its power consumption is 2.2 watts, and its noise level is 7 pT per root Hz at 1 Hz.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".