Auroral E-region electron density height profile modificationby electric field driven vertical plasma transport:some evidence in EISCAT CP-1 data statistics
Bibliographic record
Abstract
Abstract. A model developed several years ago by Huuskonen et al. (1984) predicted that vertical transport of ions in the nocturnal auroral E-region ionosphere can shift the electron density profiles in altitude during times of sufficiently large electric fields. If the vertical plasma transport effect was to operate over a sufficiently long enough time, then the real height of the E-region electron maximum should be shifted some km upwards (downwards) in the eastward (westward) auroral electrojet, respectively, when the electric field is strong, exceeding, say, 50 mV/m. Motivated by these predictions and the lack of any experimental verification so far, we made use of the large database of the European Incoherent Scatter (EISCAT) radar to investigate if the anticipated vertical plasma transport is at work in the auroral E-region ionosphere and thus to test the Huuskonen et al. (1984) model. For this purpose a new type of EISCAT data display was developed which enabled us to order a large number of electron density height profiles, collected over 16 years of EISCAT operation, according to the electric field magnitude and direction as measured at the same time at the radar's magnetic field line in the F-region. Our analysis shows some signatures in tune with a vertical plasma transport in the auroral E-region of the type predicted by the Huuskonen et al. model. The evidence brought forward is, however, not unambiguous and requires more rigorous analysis. Key words. Ionosphere (auroral ionosphere; plasma convection; electric fields and currents)
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".