Occurrence of F region echoes for the polar cap SuperDARN radars
Bibliographic record
Abstract
Abstract Observations by six Super Dual Auroral Radar Network (SuperDARN) polar cap radars, three in the northern hemisphere and three in the southern hemispheres, are considered to assess F region echo occurrence rates over solar, season, and day cycles and to establish relationship between the echo occurrence rate and the background electron density and plasma flow velocity magnitude. The echo occurrence rate is shown to increase toward the solar cycle maximum, more distinctly on the nightside, consistent with a general trend of the background electron density. Over the last 5 years, the echo occurrence rates decline at a rate of 5–10% per year. The pattern of seasonal and diurnal variations in echo occurrence is found to be consistent with previous SuperDARN publications. Minor dips in echo occurrence rate are observed in winter solstices, and these are related to an overall decrease in the electron density. In most of the time sectors, the echo occurrence rate increases with the electron density but only up to a certain threshold value after which the dependence saturates. The level of the saturation depends on season, local time, and average plasma flow velocity magnitude. For the summer daytime observations, the echo occurrence rate correlates with variations of both electron density and plasma flow velocity magnitude.
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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".