High‐Latitude Plasma Convection Based on SuperDARN Observations and the Locally Divergence Free Criterion
Bibliographic record
Abstract
Abstract A new technique for estimating the global‐scale pattern of magnetospheric convection in the ionosphere is presented. The technique uses the Super Dual Auroral Radar Network line‐of‐sight velocity observations combined with an empirical convection model and the assumption that the resulting velocity field is divergence free. In contrast to other techniques for convection estimation, it does not express the velocity field in terms of known basis vectors and it does not assume that the velocity can be determined from a static potential. The velocity is estimated by applying Bayesian inverse theory to the input data, model, and constraints. Linear equations for the plasma velocity at every point in the domain are solved simultaneously in a least squares sense. Application of the technique results in convection patterns with spatial resolution equal to the calculation grid spacing. The resulting patterns conform with expectations based on the observed interplanetary magnetic field conditions and display features that show close correspondence to simultaneously observed features in the auroral luminosity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".