A self-consistent estimate of O<sup>+</sup> + N<sub>2</sub> − rate coefficient and total EUV solar flux with λ < 1050 Å using EISCAT observations
Bibliographic record
Abstract
Abstract. There are differences between existing models of solar EUV with λ < 1050 Å and between laboratory measurements of the O+ + N2 – reaction rate coefficient, both parameters being crucial for the F2-region modeling. Therefore, indirect aeronomic estimates of these parameters may be useful for qualifying the existing EUV models and the laboratory measured O+ + N2 – rate coefficient. A modified self-consistent method for daytime F2-region modeling developed by Mikhailov and Schlegel was applied to EISCAT observations (32 quiet summer and equinoctial days) to estimate the set of main aeronomic parameters. Three laboratory measured temperature dependencies for the O+ + N2 – rate coefficient were used in our calculations to find self-consistent factors both for this rate coefficient and for the solar EUV flux model from Nusinov. Independent of the rate coefficient used, the calculated values group around the temperature dependence recently measured by Hierl et al. in the 850–1400 K temperature range. Therefore, this rate coefficient may be considered as the most preferable and is recommended for aeronomic calculations. The calculated EUV flux shows a somewhat steeper dependence on solar activity than both, the Nusinov and the EUVAC models predict. In practice both EUV models may be recommended for the F2-region electron density calculations with the total EUV flux shifted by ±25% for the EUVAC and Nusinov models, correspondingly.Key words: Ionosphere (ion chemistry and composition; ionosphere atmosphere interactions; modeling and forecasting)
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".