Characterization of Equatorial Low Latitude Ionospheric Scintillation of GPS Signals: An E-POP Experiment
Bibliographic record
Abstract
Ionospheric irregularities are a major error source in GNSS positioning and navigation as they affect trans-ionospheric signal propagation. They cause random, rapid fluctuations in the intensity and phase of the received signal, referred to as ionospheric scintillations. From a global point of view, GNSS signal scintillations are more severe and frequent in the equatorial region and during post-sunset hours. Characterizing irregularities that interfere most with navigation signals requires high-temporal resolution of measurements. In this work we utilize high-rate upward-looking measurements accomplished by the GAP RO receiver on CASSIOPE (Swarm Echo) satellite to study GPS signal scintillations and irregularities associated with them. This was done by reorienting CASSIOPE by approximately 90 degrees for short periods during November and December, 2019 while it passed through low-latitude region during post-sunset hours local time. High-rate GAP RO measurements provide a unique opportunity to investigate small-scale irregularities that are responsible for signal scintillations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".