Substorm dependence of plasmaspheric hiss
Bibliographic record
Abstract
We analyze wave and particle data from the CRRES satellite to determine the variability of plasmaspheric hiss (0.1 < f < 2 kHz) with respect to substorm activity as measured by AE *, defined as the maximum value of the AE index in the previous 3 hours. The study is relevant to modeling the acceleration and loss of relativistic electrons during storms and understanding the origin of the waves. The plasmaspheric hiss amplitudes depend on spatial location and susbtorm activity, with the largest waves being observed during high levels of substorm activity. Our survey of the global distribution of hiss indicates a strong day‐night asymmetry with two distinct latitudinal zones of peak wave activity primarily on the dayside. Equatorial hiss (∣λ m ∣ < 15°) is strongest during active conditions ( AE * > 500 nT), with an average amplitude of 40 ± 1 pT observed in the region 2 < L < 4 from 0600 to 2100 MLT. Midlatitude (∣λ m ∣ > 15°) hiss is strongest during active conditions with an average amplitude of 47 ± 2 pT in the region 2 < L < 4 from 0800 to 1800 MLT but extending out beyond L = 6 from 1200 to 1500 MLT. Equatorial hiss at 600 Hz has minimum cyclotron resonant energies ranging from ∼20 keV at L = 6 to ∼1 MeV at L = 2, whereas midlatitude hiss at 600 Hz has minimum resonant energies ranging from ∼50 keV at L = 6 to ∼2 MeV at L = 2. The enhanced equatorial and midlatitude hiss emissions are associated with electron flux enhancements in the energy range of tens to hundreds of keV, suggesting that these electrons are the most likely source of plasmaspheric hiss. The enhanced levels of plasmaspheric hiss during substorm activity will lead to increased pitch‐angle scattering of energetic electrons and may play an important role in relativistic electron dynamics during storms.
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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 | 0.001 |
| 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".