Investigation in the Variations of Ionospheric f0F2 due to Sunspot Numbers over Wakkanai using EDA Technique
Bibliographic record
Abstract
In this research article, the authors have implemented the Exploratory Data Analysis (EDA) techniques to examine the deviation of the monthly median noon and midnight values of the critical frequency of F2 layer ionosphere (i.e. f0F2) at the Wakkanai station (45.39°N, 141.68°E), Japan, during sunspot cycle 21st (1976-1986) and 23rd (1996-2008). Primarily, univariate analysis has been done, which shows the variations in f0F2 at different local times, seasons and in the range of sunspot numbers (SSN), in which winter and semi-annual anomalies are detected in the months of December and March respectively. Secondly, the regression analysis is being used as a bivariate data analysis. The results proved a significantly nonlinear relationship exists between f0F2 and SSN. In both solar cycles, saturation effects are seen in the month of March during the noontime period and immensely in June during the midnight time. The behavior of the ionosphere has been studied for different latitudes, seasonal effects and sunspot dynamic conditions, in which this paper plays an essential role in it.
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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 | 0.001 | 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) | 0.000 | 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 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".