Characterization of auroral radar power spectra and autocorrelation functions
Why this work is in the frame
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Bibliographic record
Abstract
Radar backscatter is a commonly used tool for studying plasma instabilities in the auroral E region. Analysis of the received signals typically involves moments of the scattered power spectrum such as total power, mean Doppler shift, and spectral width; in some cases the spectral asymmetry may also be of interest. This paper presents the steps required to estimate spectral moments directly from the autocorrelation function, and some advantages and limitations of working in the lag domain are discussed. Recent measurements of auroral spectra at UHF (440 and 933 MHz) are used to motivate the discussion and as test cases. The utility of parametric models is also studied with an emphasis on determining whether spectra are more nearly Gaussian or Lorentzian. A model autocorrelation function is introduced, with spectral characteristics similar to a Voigt distribution but a more convenient functional form.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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 it