GPS phase scintillation and proxy index at high latitudes during a moderate geomagnetic storm
Bibliographic record
Abstract
Abstract. The amplitude and phase scintillation indices are customarily obtained by specialised GPS Ionospheric Scintillation and TEC Monitors (GISTMs) from L1 signal recorded at the rate of 50 Hz. The scintillation indices S4 and σΦ are stored in real time from an array of high-rate scintillation receivers of the Canadian High Arctic Ionospheric Network (CHAIN). Ionospheric phase scintillation was observed at high latitudes during a moderate geomagnetic storm (Dst = −61 nT) that was caused by a moderate solar wind plasma stream compounded with the impact of two coronal mass ejections. The most intense phase scintillation (σΦ ~ 1 rad) occurred in the cusp and the polar cap where it was co-located with a strong ionospheric convection, an extended tongue of ionisation and dense polar cap patches that were observed with ionosondes and HF radars. At sub-auroral latitudes, a sub-auroral polarisation stream that was observed by mid-latitude radars was associated with weak scintillation (defined arbitrarily as σΦ < 0.5 rad). In the auroral zone, moderate scintillation coincided with auroral breakups observed by an all-sky imager, a riometer and a magnetometer in Yellowknife. To overcome the limited geographic coverage by GISTMs other GNSS data sampled at 1 Hz can be used to obtain scintillation proxy indices. In this study, a phase scintillation proxy index (delta phase rate, DPR) is obtained from 1-Hz data from CHAIN and other GPS receivers. The 50-Hz and 1-Hz phase scintillation indices are correlated. The percentage occurrences of σΦ > 0.1 rad and DPR > 2 mm s−1, both mapped as a function of magnetic latitude and magnetic local time, are very similar.
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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) | 0.001 | 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".