First results from the Langmuir Probes on the Swarm satellites
Bibliographic record
Abstract
Langmuir Probes (LP) are well-proven simple instruments allowing to estimate the electron density (Ne) and temperature (Te) of a plasma. They are also used to estimate the electric potential of satellites to the benefit of other instruments and technical systems. On the Swarm satellites the LPs are part of the Electric Field Instruments (EFI) featuring thermal ion imagers (TII) measuring 3-d ion distributions. The main task of the Langmuir probes is to provide measurements of spacecraft potentials influencing the ions before they enter the TIIs. In addition also electron density (Ne) and temperature (Te) are estimated from EFI LP data. The design of the Swarm LP includes a standard current sampling under sweeps of the bias voltage, and also, for most of the time, a novel ripple technique yielding derivatives of the current-voltage characteristics at three points in a rapid cycle. In normal mode the time resolution of the Ne and Te measurements so becomes only 0.5 s. We show first Ne and Te estimates from the EFI LPs obtained. The data feature very low instrumental noise thanks to the ripple technique. The LP data are compared with observations by incoherent scatter radars, namely EISCAT UHF, VHF, the ESR, and also Arecibo.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".