Observation of subsecond variations in auroral region total electron content using 100 Hz sampling of GPS observables
Bibliographic record
Abstract
Abstract First ever auroral region total electron content (TEC) measurements at 100 Hz using a Septentrio PolaRxS Pro receiver are analyzed to discover ionospheric signatures which would otherwise be unobtainable with the frequently used lower sampling rates. Two types of variations are observed: small‐magnitude (amplitude) variations, which are present consistently throughout the data set, and larger‐magnitude (amplitude) variations, which are less frequent. Small‐amplitude TEC fluctuations are accounted for by the receiver phase jitter. However, estimated secondary ionospheric effects in the calculation of TEC and the receiver phase jitter were unable to account for the larger‐amplitude TEC fluctuations. These variations are also accompanied by fluctuations in the magnetic field, which seems to indicate that these fluctuations are real and of geophysical significance. This paper presents a technique and the capability of high‐rate TEC measurements in the study of auroral dynamics. Further detailed study is needed to identify the cause of these subsecond TEC fluctuations and associated magnetic field fluctuations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".