Experimental Evidence on the Dependence of the Standard GPS Phase Scintillation Index on the Ionospheric Plasma Drift Around Noon Sector of the Polar Ionosphere
Bibliographic record
Abstract
Abstract First experimental proof of a clear and strong dependence of the standard phase scintillation index (σφ) derived using Global Positioning System measurements on the ionospheric plasma flow around the noon sector of polar ionosphere is presented. σφ shows a strong linear dependence on the plasma drift speed measured by the Super Dual Auroral Radar Network radars, whereas the amplitude scintillation index (S4) does not. This observed dependence can be explained as a consequence of Fresnel frequency dependence of the relative drift and the used constant cutoff frequency (0.1 Hz) to detrend the data for obtaining standard σφ. The lack of dependence of S4 on the drift speed possibly eliminates the plasma instability mechanism(s) involved as a cause of the dependence. These observations further confirm that the standard phase scintillation index is much more sensitive to plasma flow; therefore, utmost care must be taken when identifying phase scintillation (diffractive phase variations) from refractive (deterministic) phase variations, especially in the polar region where the ionospheric plasma drift is much larger than in equatorial and midlatitude regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".