Comparisons Between E-region Coherent Scatter and Swarm-E Fast Auroral Imager Measurements
Bibliographic record
Abstract
The Ionospheric Continuous-wave E-region Bistatic Experimental Auroral Radar (ICEBEAR) is a VHF coherent scatter radar that makes measurements of the E-region ionosphere with a field of view centered on ≈ 58°N, 106°W. This overlaps with the Saskatoon SuperDARN radar field of view, providing the opportunity for multi-frequency coherent scatter radar measurements in a similar region. In conjunction with these coherent scatter radar measurements, the Swarm-E, or e-POP, satellite Fast Auroral Imager (FAI) has been used to make measurements of auroral emissions in the 650-1100 nm wavelength band over the same field of view. The primary emission species in this wavelength range are N2, O2, and N2+, which correspond to energetic charged particle precipitation penetrating into the lower altitudes of the ionosphere. This makes the FAI a great instrument for comparison studies with E-region coherent scatter. In addition to this, the FAI is able to be slewed to a location allowing for extended conjunction windows between the imager and the coherent scatter radars. With recent advances in radar hardware and processing the temporal and spatial resolutions of these different instruments are becoming comparable (~ 1 s, 1.5 km), providing an excellent opportunity to study plasma density irregularities in the E-region ionosphere in great detail. Comparisons between the coherent scatter radar and FAI measurements are presented, providing insights into how E-region plasma density irregularities correspond to the location of auroral emissions at 650-1100 nm wavelengths.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".