Intense Energetic Electron Precipitation Caused by the Self‐Limiting of Space Radiation
Bibliographic record
Abstract
Abstract Understanding intense electron precipitation is crucial for characterizing radiation belt loss and assessing related impacts on the atmosphere. We investigate the evolution of electron flux during an ensemble of 70 geomagnetic storms, focusing on equatorial and low‐Earth orbit observations of trapped and precipitating ∼30–100 keV energy electrons. We reveal that the most intense electron precipitation is associated with equatorial flux capping through self‐limiting processes, for example, as described theoretically by Kennel and Petschek (1966, https://doi.org/10.1029/jz071i001p00001 ). Our results indicate that the most intense electron precipitation is caused by electron injections associated with self‐limiting processes. Dawn side injections are observed to have fluxes that exceed the Kennel‐Petschek limit, consistent with the excitation of strong chorus waves and resulting in intense precipitation and return of the trapped flux to the Kennel‐Petschek limit. Our results clearly demonstrate the important role of self‐limiting processes in affecting the dynamics of newly injected electrons and driving intense electron precipitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".