Volume cross section of auroral radar backscatter and RMS plasma fluctuations inferred from coherent and incoherent scatter data: a response on backscatter volume parameters
Bibliographic record
Abstract
Abstract. Norway and Finland STARE radar measurements in the eastward auroral electrojet are combined with EISCAT CP-1 measurements of the electron density and electric field vector in the common scattering volume to investigate the variation of the auroral radar volume cross section (VCS) with the flow angle of observations (radar look direction with respect to the E×B electron drift). The data set available consists of ~6000 points for flow angles of 40–85° and electron drifts between 500 and 2000 m s−1. The EISCAT electron density N(h)-profile data are used to estimate the effective electron density, aspect angle and thickness of the backscattering layer. It is shown that the flow angle variation of the VCS is rather weak, only ~5 dB within the range of the considered flow angles. The VCS values themselves respond almost linearly to the square of both the electron drift velocity magnitude and the effective electron density. By adopting the inferred shape of the VCS variation with the flow angle and the VCS dependence upon wavelength, the relative amplitude of electrostatic electron density fluctuations over all scales is estimated. Inferred values of 2–4 percent react nearly linearly to the electron drift velocity in the range of 500–1000 m s−1 but the rate of increase slows down at electron drifts >1000 m s−1 and density fluctuations of ~5.5 percent due to, perhaps, progressively growing nonlinear wave losses.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".