Statistical patterns in X‐ray and UV auroral emissions and energetic electron precipitation
Bibliographic record
Abstract
Statistical auroral images from the UV and X‐ray imagers on the Polar spacecraft were compared with each other and with statistical distributions of energetic auroral electron energy fluxes from two different energy ranges: 50 eV to 20 keV and 30 keV to 2 MeV. The individual statistical auroral ovals each had unique features absent in some or all of the other ovals; however, the differences were consistent with the known instrument energy responses, the motion of magnetospheric particles in the inner magnetosphere, and the spectral characteristics of the auroral particles. Separation of the statistical results by Kp showed little difference in the auroral distributions other than in intensity. However, separation of the X‐ray data by Dst showed significant differences, and there were indications that the UV statistical data show a similar dependence. X‐ray emissions, on average, were more intense in the evening sector for Dst > 0, associated with isolated substorm activity and substorm injections, and in the morning sector for Dst < 0, associated with geomagnetic storm activity and strong magnetospheric convection.
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 | 0.002 |
| 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 | 0.000 | 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".