A statistical approach to determining energetic outer radiation belt electron precipitation fluxes
Bibliographic record
Abstract
Abstract Subionospheric radio wave data from an Antarctic‐Arctic Radiation‐Belt (Dynamic) Deposition VLF Atmospheric Research Konsortia (AARDDVARK) receiver located in Churchill, Canada, is analyzed to determine the characteristics of electron precipitation into the atmosphere over the range 3 < L < 7. The study advances previous work by combining signals from two U.S. transmitters from 20 July to 20 August 2010, allowing error estimates of derived electron precipitation fluxes to be calculated, including the application of time‐varying electron energy spectral gradients. Electron precipitation observations from the NOAA POES satellites and a ground‐based riometer provide intercomparison and context for the AARDDVARK measurements. AARDDVARK radiowave propagation data showed responses suggesting energetic electron precipitation from the outer radiation belt starting 27 July 2010 and lasting ~20 days. The uncertainty in >30 keV precipitation flux determined by the AARDDVARK technique was found to be ±10%. Peak >30 keV precipitation fluxes of AARDDVARK‐derived precipitation flux during the main and recovery phase of the largest geomagnetic storm, which started on 4 August 2010, were >10 5 el cm −2 s −1 sr −1 . The largest fluxes observed by AARDDVARK occurred on the dayside and were delayed by several days from the start of the geomagnetic disturbance. During the main phase of the disturbances, nightside fluxes were dominant. Significant differences in flux estimates between POES, AARDDVARK, and the riometer were found after the main phase of the largest disturbance, with evidence provided to suggest that >700 keV electron precipitation was occurring. Currently the presence of such relativistic electron precipitation introduces some uncertainty in the analysis of AARDDVARK data, given the assumption of a power law electron precipitation spectrum.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".