Comparison of F‐Region Ion Velocities Measured by Swarm Satellites and EISCAT Radars
Bibliographic record
Abstract
Abstract Ionospheric ion flow velocities measured by the Swarm satellites are compared with the ion velocities estimated from the European Incoherent Scatter (EISCAT) radar measurements in Tromsø and on Svalbard. A comparison is carried out between the cross‐track horizontal ion velocity component given by the Swarm Electric Field Instrument and the corresponding component by the EISCAT radars. This paper describes the comparison procedure between the two very different measurement methods and discusses the challenges in the comparison. Several events are found with eastward or westward ion flow channels that exceed 1,000 m/s. The example events shown occur between the Region 1 and 2 current sheets in the afternoon and post‐midnight sectors, and one event in the vicinity of the dayside cusp. However, since the flow channels are relatively narrow and short‐lived, it is difficult to capture the ion flow channel by ground‐based radar measurements. A Linear fit for the selected conjunction events shows that on average, the Swarm ion velocities are larger than EISCAT ion velocities by a factor of . The main reason for the smaller ion velocity estimates by EISCAT compared to Swarm is likely the coarser spatial and temporal resolution of the radar experiment, which prevents measurement of the narrow ionospheric flow channels. Ion composition at Swarm altitudes may also play a minor role by affecting the standard Swarm analysis velocity values.
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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 | 0.002 | 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".