Characteristics and longitudinal extent of VLF quasi-periodic emissions using multi-point ground-based observations
Bibliographic record
Abstract
Abstract Quasi-periodic (QP) emissions are a type of magnetospheric ELF/VLF waves characterized by a periodic intensity modulation ranging from tens of seconds to several minutes. Here, we present 63 QP events observed between January 2017 and December 2018. Initially detected at the VLF receiver in Kannuslehto, Finland (KAN, MLAT = 67.7°N, L = 5.5), we proceeded to check whether these events were simultaneously observed at other subauroral receivers. To do so we used the following PWING stations: Athabasca (ATH, MLAT = 61.2°N, L = 4.3, Canada), Gakona (GAK, MLAT = 63.6°N, L = 4.9, Alaska), Husafell (HUS, MLAT = 64.9°N, L = 5.6, Iceland), Istok (IST, MLAT = 60.6°N, L = 6.0, Russia), Kapuskasing (KAP, MLAT = 58.7°N, L = 3.8, Canada), Maimaga (MAM, MLAT = 58.0°N, L = 3.6, Russia), and Nain (NAI, MLAT = 65.8°N, L = 5.0, Canada). We found that: (1) QP emissions detected at KAN had a relatively longer observation time (1–10 h) than other stations, (2) 11.3% of the emissions at KAN were observed showing one-to-one correspondence at IST, and (3) no station other than IST simultaneously observed the same QP emission as KAN. Since KAN and IST are longitudinally separated by 60.6°, we estimate that the maximum meridional spread of conjugated QP emissions should be close to 60° or 4 MLT. Comparison with geomagnetic data shows half of the events are categorized as type II, while the rest are mixed (type I and II). This study is the first to clarify the longitudinal spread of QP waves observed on the ground by analyzing simultaneous observations over 2 years using multiple ground stations. Graphical Abstract
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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 | 0.001 | 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".