High-latitude GPS phase scintillation and cycle slips during high-speed solar wind streams and interplanetary coronal mass ejections: a superposed epoch analysis
Bibliographic record
Abstract
Results of a superposed epoch (SPE) analysis of occurrence of phase scintillation and cycle slips at high latitudes keyed by arrival times of high-speed solar wind streams (HSS) and interplanetary coronal mass ejections (ICME) for years 2008 to 2012 are presented. Phase scintillation index σ Φ is obtained in real time from L1 signal recorded at the rate of 50 Hz by specialized global positioning system (GPS) ionospheric scintillation and total electron content (TEC) monitors (GISTMs) deployed as a part of the Canadian High Arctic Ionospheric Network (CHAIN). The phase scintillation, mapped as a function of magnetic latitude and magnetic local time, occurs predominantly on the dayside in the cusp and in the nightside auroral oval. The scintillation occurrence peaks on days of HSS or ICME impacts at the Earth's magnetosphere and tapers off a few days later, which is similar to day-to-day variability of geomagnetic activity and riometer absorption at high latitudes. ICMEs that are identified as magnetic clouds are significantly more geoeffective than HSSs and ICMEs with no or weak magnetic cloud characteristics. On their arrival day, magnetic clouds result in higher occurrence, and thus probability, of scintillation in the nightside auroral zone. The SPE analysis results are used to obtain cumulative probability distribution functions for the phase scintillation occurrence that can be employed in probabilistic forecast of phase scintillation at high latitudes.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".