A Polar‐Cap Patch Detection Algorithm for the Advanced Modular Incoherent Scatter Radar System
Bibliographic record
Abstract
Abstract We introduce an algorithm to detect polar‐cap patches in an Advanced Modular Incoherent Scatter Radar data set, using the Resolute Bay Incoherent Scatter Radar—North. Patches are detected by comparing plasma density (ne) measurements along each radar beam to a 30‐min running average of the median ne within the field‐of‐view. The algorithm is tested and shown to be an effective tool for polar‐cap patch studies. It is then used to conduct a survey of patches over Resolute Bay for two separate periods of time centered on March and December of 2010. The survey shows that polar‐cap patches are almost always present in both sunlit and nighttime conditions. However, the population is subdued during the day. The patch densities are found to vary by as much as an order of magnitude throughout the day. Their ion temperature is relatively constant, only varying by 100 K between the sunlit and nighttime conditions. By contrast, their electron temperature is very sensitive to the solar zenith angle and changes dramatically around sunrise.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".