On the nature of ULF wave power during nightside auroral activations and substorms: 1. Spatial distribution
Bibliographic record
Abstract
[1] We present the results of a statistical analysis of ground-based magnetometer Ultra Low Frequency (ULF) wave power and polarization during substorm expansion phase onset in three ULF wave bands, the longer-period Pi1 (10–40 s) band, the Pi1-2 (24–96 s) band, and Pi2 (40–150 s) wave band, in order to determine whether these wave bands are statistically disparate phenomena during expansion phase onset. Utilizing over 800 nightside auroral activations and substorms identified by the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite, we characterize the two-dimensional spatial distribution of ULF wave power, angle of azimuth, and ellipticity with respect to the spatial and temporal onset of the initial auroral brightening as observed by IMAGE. We determine the statistical ULF wave power spectra observed during substorm expansion phase onset and characterize the spatial decay scales of ULF wave power, in each of the three ULF wave bands, as a function of latitude and longitude. In general, we find that the spatial distribution of ULF wave power, angle of azimuth, and ellipticity in each of the three ULF bands is consistent with previous case studies and that the Pi1-2 and Pi2 wave bands are remarkably similar. Additionally, we find that the spatial decay scales of ULF wave power in the long-period Pi1, the Pi1-2, and the Pi2 bands are surprisingly similar. Finally we show that the statistical ULF wave power spectrum is characteristic of a power law with no preferred frequency or discontinuity to differentiate between the three ULF wave bands, demonstrating the importance of studying the entire ULF spectrum during substorm expansion phase onset.
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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 | 0.002 |
| 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".