Statistical Study of Whistler‐Mode Waves and Expected Pitch Angle Diffusion Rates During Dispersionless Electron Injections
Bibliographic record
Abstract
Energetic electron injections can generate or amplify electromagnetic waves such as whistler-mode waves. These waves can resonantly interact with available particles to affect their equatorial pitch angle. This process can be considered as a diffusion that scatters particles into the loss cone. This study investigates whistler-mode wave generation in conjunction with electron injections using in situ wave measurements by the Time History of Events and Macroscale Interactions during Substorms mission during 2011-2020. We characterize the whistler-mode wave behavior associated with 733 selected dispersionless electron injections and dipolarizing flux bundles (DFBs). We observe intense wave activity and strong diffusion associated with only the top 5% and 10% of the selected injection events, respectively. We also study the wave activity when there is a sharp rise in the northward component of the magnetic field around the injection time (DFBs). In this case, the generated wave powers increase, and the power change is at least two times greater than non-DFB injections.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".