The dawn and dusk electrojet response to substorm onset
Bibliographic record
Abstract
Abstract. We have investigated the time delay between substorm onset and related reactions in the dawn and dusk ionospheric electrojets, clearly separated from the nightside located substorm current wedge by several hours in MLT. We looked for substorm onsets occurring over Greenland, where the onset was identified by a LANL satellite and DMI magnetometers located on Greenland. With this setup the MARIA magnetometer network was located at dusk, monitoring the eastward electrojet, and the IMAGE chain at dawn, for the westward jet. In the first few minutes following substorm onset, sudden enhancements of the electrojets were identified by looking for rapid changes in magnetograms. These results show that the speed of information transfer between the region of onset and the dawn and dusk ionosphere is very high. A number of events where the reaction seemed to preceed the onset were explained by either unfavorable instrument locations, preventing proper onset timing, or by the inner magnetosphere's reaction to the Earthward fast flows from the near-Earth neutral line model. Case studies with ionospheric coherent (SuperDARN) and incoherent (EISCAT) radars have been performed to see whether a convection-induced electric field or enhanced conductivity is the main agent for the reactions in the electrojets. The results indicate an imposed electric field enhancement.Key words: Ionosphere (auroral ionosphere; electric fields and currents) - Magnetospheric physics (storms and substorms)
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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 | 0.000 | 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) | 0.001 | 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".