Multipulse and double‐pulse velocities of Scandinavian Twin Auroral Radar Experiment (STARE) echoes
Bibliographic record
Abstract
The Scandinavian Twin Auroral Radar Experiment (STARE) coherent radars are a powerful instrument for studying auroral zone plasma convection. In recent years the STARE radars have been collecting both double‐pulse (DP) and multipulse (MP) data to measure the Doppler velocity of auroral echoes. We assess here DP‐MP measurements for eight events covering 28 hours of operation. More often, there is a reasonable agreement between the DP and MP velocities. Exceptions are afternoon‐evening observations for which the Finland radar DP velocity is nearly half the MP velocity obtained through fitting of the autocorrelation function of a received signal (ACF‐FIT), although the DP and MP1 (first lag) velocities are in reasonable agreement. We demonstrate that for periods with strong differences between the DP and MP ACF‐FIT velocities the spectra are strongly asymmetric, and the phase angle–lag number dependence is nonlinear with a slower rate of angle increase at small‐number lags (<3) and a faster rate of angle increase at larger‐number lags. Contrary to the DP velocity, the MP ACF‐FIT velocity (obtained in some cases without one or two first‐lag data) is fairly close to the spectral power peak and power‐weighted (over spectrum) velocity. In an attempt to understand the DP‐MP velocity differences, we consider the role of the asymmetry of observed spectra and show that it can explain the discrepancies but only partially. As another potentially important effect, we consider the possibility of weak, but not negligible, cross‐range correlation between the signals coming from the target and aliasing volumes that are closely spaced for the current STARE mode of operation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".