Long‐term variations in the intensity of polar cap plasma flows inferred from SuperDARN
Bibliographic record
Abstract
Abstract Multiyear (1995–2013) velocity data collected by the Super Dual Auroral Network (SuperDARN) HF radars are considered to investigate the diurnal, seasonal, and solar cycle variation of the polar cap plasma flow speed. By considering monthly data sets, we show that the flows are systematically faster in the dawn/prenoon sector. The effect is particularly strong for interplanetary magnetic field (IMF) Bz < 0, By > 0 and in summer months. For Bz < 0, the flow speed increases with intensification of the IMF transverse component Bt at a rate of 20–30 m/s/nT during near noon summer hours. The dependence is weaker for other seasons and away from noon. For IMF Bz > 0, the flow speed response to the increase in Bt is weak. Despite the general sensitivity of the flow speed to Bt intensity and season, the speed for specific IMF bins and seasons or the speed averaged over a year does not change much over the solar cycle. Overall, the velocity is reduced during years of lowest solar activity, but a progression of the effect throughout the solar cycle was not observed. Inferred diurnal and seasonal trends of the polar cap flow speed are generally consistent with variations in the occurrence of VHF echoes whose onset depends on the strength of the ionospheric electric field or equivalently the magnitude of the plasma flow speed.
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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 | 0.000 | 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".