Comparison of the magnetic equivalent convection direction and ionospheric convection observed by the SuperDARN radars
Bibliographic record
Abstract
Abstract. SuperDARN radar and high-latitude magnetometer observations are used to statistically investigate quality of the convection direction estimates from magnetometer data if assumption is made that the magnetic equivalent convection vector (MEC) corresponds to the convection direction. The statistics includes five full days, ~75 000 of joint individual measurements for different seasons. It is demonstrated that the best (worst) agreement between the MEC and ionospheric convection occurs for the sunlit, summer (dark, winter) ionosphere. Overall, the MEC direction is reasonable (deviates less than 45° from the SuperDARN direction) in at least ~55% of points and it is better for the latitudes of the auroral oval. In terms of the magnetic local time, the agreement is the best (worst) in the dusk (early morning) sector. Possible reasons for differences between the MEC and ionospheric convection directions are discussed.
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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 | 0.000 |
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".