Polar Ionospheric Large‐Scale Structures and Dynamics Revealed by TEC Keogram Extracted From TEC Maps
Bibliographic record
Abstract
Abstract A method named total electron content (TEC) keogram is introduced for surveying the large‐scale irregularities continuously in the polar ionosphere. The TEC keogram is developed from a movie of TEC maps along various meridian lines from the dayside to the nightside across the magnetic pole, trying to identify and track several types of ionospheric structures. Through two examples, a clear train of polar cap patches are identified from TEC keogram and confirmed by SuperDARN radar observations. The motion speed of these patches estimated from this tool agrees with SuperDARN radar measurements. Then, the motions of patches relative to the background convection through the whole polar cap are statistically studied for the first time. Moreover, the occurrence dependence of fully tracked patches on months, UT hours, and interplanetary magnetic field conditions is generally consistent with previous reports. These results suggest that the TEC keogram offers a power tool for continuous monitoring and studying of large‐scale plasma irregularities in the polar ionosphere.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".