Statistical Characteristics of Polar Cap Patches Observed by RISR‐C
Bibliographic record
Abstract
Abstract Polar cap “patches” are ~100 to 1,000 km islands of high‐density plasma at polar latitudes, which can cause scintillation to communication and navigation signals. An automatic algorithm for patch identification has been developed and applied to the observations from the Resolute Bay Incoherent Scatter Radar‐Canada during January to March and September to December, 2016. Four hundred thirty‐seven patches have been identified, and their statistical characteristics have been studied, including their occurrence rate as a function of magnetic local time (MLT) and statistical profiles of plasma parameters at different MLT sectors. About 60% of the patches are observed between 1200 and 2400 MLT, consistent with earlier observations near this latitude (~82° MLat) using different instruments. Superposed epoch analysis has been used to study the vertical profiles of electron density and temperature, ion temperature, vertical velocity, and flux measured within the patches where the density peaks. The patch median density is higher than the sector median with a ratio of ~1.8–2.1 at the altitude of F‐region density peak. Meanwhile, the patch electron temperature is typically lower than the sector median between ~200 and 450 km with the largest difference near noon (~380 K). In contrast, the ion temperature profile of the patches does not show obvious differences except in the noon sector, where the ion temperature is about 150 K higher than the sector median at ~360 km. Additionally, downward ion fluxes with peak exceeding ~10 13 m −2 s −1 are found in the patches between ~200 and 400 km at all MLT sectors.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".