Thermal Electron Temperature Measurements from the Freja Cold Plasma Analyzer
Bibliographic record
Abstract
The Freja Cold Plasma Analyzer (CPA) is a hemispherical electrostatic analyzer which forms 2-D, energy/arrival angle images of low-energy (< 200 eV) particle distribution functions. In addition to its 2-D imaging capability, the CPA is unique in that its sensor head is displaced from the spacecraft on a 2 m boom which allows control of the probe-to-plasma potential, thereby compensating for variations in spacecraft potential. Furthermore, the detector biases can be set to measure either positively or negatively charged particle species. This study emphasizes temperature measurements of the core electron population (∼ 1 eV) which are difficult to make since, among other reasons, they are affected by spacecraft charging and are susceptible to contamination from photoelectrons and finite gyroradius effects. We demonstrate that the CPA sensor does detect the core population by showing that probe-to-plasma potential changes of only a fraction of 1 V cause large changes in the electron flux measured at the detector anode. The relation between detector current and sensor bias comprises a modified Langmuir curve, which in contrast to standard Langmuir measurements results from a single particle species only (electrons) and from particles which are restricted in energy (0-70 eV) and in arrival angle to within ±4° of the detector plane. The modified Langmuir curve can be compared to a standard Langmuir curve formed by measuring current onto the external skin of the sensor, which contains contributions from both electrons and ions at all energies and over a wide angular acceptance. Somewhat surprisingly, the two methods agree fairly well in the sunlit portion of a sample orbit, i.e. in the presence of a background photoelectron population, but differ by up to a factor of two in the dark part of the orbit.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".