Aspect angle dependence of the <i>E</i> region irregularity velocity at large flow angles
Bibliographic record
Abstract
We present the Doppler velocity observations of 1‐m plasma waves in the auroral E region by the Scandinavian Twin Auroral Radar Experiment (STARE) Norway VHF coherent radar in the context of simultaneous and coincident measurements of electron and ion drift velocities determined by the European Incoherent Scatter (EISCAT) tristatic radar facility. The measurements were performed in the afternoon sector (1500–2000 MLT) at seven locations along the STARE radar beam 2 with different values of the magnetic off‐perpendicular (aspect) angle α between 0.48° and 2.63° and at large angles with respect to the electron background drift (θ = 55°–90°). It is demonstrated that the STARE line‐of‐sight velocity, normalized to the EISCAT‐derived electron drift speed at large flow angles, exhibits a decrease with increasing aspect angle, and the rate of decrease is investigated as a function of the flow angle. We also compare the STARE velocity with the electron and ion drift velocity components along the STARE radar beam look direction and show that, at large aspect angles, the E region velocity is correlated (anticorrelated) with the ion (electron) drift velocity component. The results are discussed in the contexts of the linear fluid theory of the modified two‐stream plasma instability and the theory of anomalous collisions.
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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) | 0.000 | 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".