Strong ambipolar‐driven ion upflow within the cleft ion fountain during low geomagnetic activity
Bibliographic record
Abstract
Abstract We investigate low‐energy (<10 eV) ion upflows (mainly O+) within the cleft ion fountain (CIF) using conjunctions of the Enhanced Polar Outflow Probe (e‐POP) satellite, the DMSP F16 satellite, the SuperDARN radar, and the Resolute Bay Incoherent Scatter Radar North (RISR‐N). The SEI instrument on board e‐POP enables us to derive ion upflow velocities from the 2‐D images of ion distribution functions with a frame rate of 100 images per second, and with a velocity resolution of the order of 25 m/s. We identify three cleft ion fountain events with very intense (>1.6 km/s) ion upflow velocities near 1000 km altitude during quiet geomagnetic activity (Kp < 3). Such large ion upflow velocities have been reported previously at or below 1000 km, but only during active periods. Analysis of the core ion distribution images allows us to demonstrate that the ion temperature within the CIF does not rise by more than 0.3 eV relative to background values, which is consistent with RISR‐N observations in the F region. The presence of soft electron precipitation seen by DMSP and lack of significant ion heating indicate that the ion upflows we observe near 1000 km altitude are primarily driven by ambipolar electric fields. DC field‐aligned currents (FACs) and convection velocity gradients accompany these events. The strongest ion upflows are associated with downward current regions, which is consistent with some (although not all) previously published results. The moderate correlation coefficient (0.51) between upflow velocities and currents implies that FACs serve as indirect energy inputs to the ion upflow process.
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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 | 0.000 |
| 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".