On the SuperDARN cross polar cap potential saturation effect
Bibliographic record
Abstract
Abstract. Variation of the cross polar cap potential (CPCP) with the interplanetary electric field (IEF), the merging electric field EKL, the Polar Cap North (PCN) magnetic index, and the solar wind-magnetosphere coupling function EC of Newell et al. (2007) is investigated by considering convection data collected by the Super Dual Auroral Radar Network (SuperDARN) in the Northern Hemisphere. Winter and summer observations are considered separately. All variations considered show close to linear trend at small values of the parameters and tendency for the saturation at large values. The threshold values starting from which the non-linearity was evident were estimated to be IEF*~EKL*~3 mV/m, PCN*~3–4, and EC*~1.5×104. The data indicate that saturation starts at larger values of the above parameters and reaches larger (up to 10 kV) saturation levels during summer. Conclusions are supported by a limited data set of simultaneous SuperDARN observations in the Northern (summer) and Southern (winter) Hemispheres. It is argued that the SuperDARN CPCP saturation levels and the thresholds for the non-linearity to be seen are affected by the method of the CPCP estimates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".