Analysis of Conjugate Satellite and Ground EMIC Wave Observations
Bibliographic record
Abstract
Electromagnetic ion cyclotron (EMIC) waves are transverse electromagnetic waves typically generated in the equatorial magnetosphere by anisotropic proton distributions. These waves can resonantly interact with multiple particle populations in the inner magnetosphere believed to be an important loss mechanism for both ring current ions and radiation belt electrons, as well as a cold plasma heating source. The spatiotemporal extent of wave activity is one of the key parameters used to quantify the effects of EMIC waves on magnetospheric plasma populations. However, from single-point spacecraft measurements or ground based observations alone, it is challenging to get the full picture of wave occurrence distributions. Due to a number of processes, ground and in situ observations of EMIC wave activity, specifically, its global occurrence, duration, and frequency often exhibit noticeable variations [1]. In particular, EMIC waves in the H+ frequency band are not always seen on the ground conjugately to locations of space observations [2]. In addition, ground and space EMIC wave distributions have different dependencies on local time, L shell, and geomagnetic activity, adding to the challenge of comparing measurements across these platforms [3]. Here we address this challenge by examining the relationship between EMIC wave occurrence and power on the Van Allen Probes and conjugate CARISMA ground magnetometer stations in the Canadian sector. We apply an automated wave detection algorithm to magnetometer data [4]. We present an analysis of long-term simultaneous EMIC wave observations in space and on the ground, and study wave propagation characteristics in the He+ and H+ frequency bands during different geomagnetic conditions.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".