The spatial localisation of storm-time ULF waves due to plasmaspheric plumes and implications for calculating radial diffusion
Bibliographic record
Abstract
The generation and propagation of Ultra Low Frequency (ULF) waves are intrinsically coupled to the cold plasma population in the terrestrial magnetosphere. During geomagnetic storms, extreme reconfigurations of the cold plasma creates a complex and dynamic system that drastically modifies this coupling. The extent and manner in which this coupling is affected remains an open question. In this report, we assess the coupling between ULF waves and cold plasmaspheric plumes during geomagnetic storms, and investigate the implications for ULF wave-driven radial transport of the outer radiation belt population. We present a series of event studies of Van Allen Probes observations. For each event, we use inferred measurements of the cold plasma density during plume crossings, in combination with magnetic and electric field observations of ULF waves. The event studies show very different, and at times contrasting, wave behaviour. This includes events where ULF waves appear to be spatially confined within plume structures. Initial estimates show that the localised patches of ULF wave power have significant implications for radial diffusion processes, and highlights the need for caution in estimating radial diffusion coefficients. We suggest that the cold plasma dynamics is an important source of uncertainty in radial diffusion models, and understanding cold plasma-ULF wave coupling is a critical area of future investigations.
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".