Inferred Ionospheric irregularity scales from amplitude scintillation
Bibliographic record
Abstract
The analysis of the structure function of a GNSS signal amplitude measured on the ground has revealed that ionospheric scintillation could be considered a proxy for ionospheric turbulence. More precisely, and in a recent report, the existence of a linear range with respect to the time lag in the structure function has been highlighted. In this context, the inertial-range analog has been determined from the analysis of a large set of scintillation events collected over several days from Pond Inlet located in the northern polar region and from Sao Paolo located at 23.2 degrees South of the Equator. At high latitude, we found that the mean value of the first-order scaling exponent is H = 0.55 ± 0.07, while a low altitude H is typically larger with H = 0.84 ±.11. This result clearly indicates that the long-time lag positive correlation remains persistent in the low latitude region. At high latitude however, both negative and positive long time lag correlation can occur. In addition, the obtained results clearly show that the inertial range analog is significantly smaller at high latitude, particularly the upper bound time lags at which the structure function deviates from linearity. This distinction may pinpoint to a difference in the ionospheric irregularity drift speed.
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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 | 0.003 |
| 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 | 0.001 | 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".