Space‐time variability of polar cap patches: Direct evidence for internal plasma structuring
Bibliographic record
Abstract
Coordinated observations of ionospheric variability near the geomagnetic pole using the Resolute Bay Incoherent Scatter Radar (RISR‐N), Super Dual Auroral Radar Network (SuperDARN) High Frequency (HF) radars, and all‐sky imagers have clarified the relative contribution of structuring mechanisms operating on polar plasma patches. From the multipoint RISR‐N observations, a three dimensional image can be constructed of the plasma parameters. The colocated coherent echoes from the SuperDARN radars provide information on field aligned irregularities, and from all‐sky imagers located in Resolute Bay, Canada and Qaanaaq, Greenland, information is obtained on the emission brightness at different wavelengths. A good correlation is found between the location of the coherent, incoherent and optical signals of patches. From the SuperDARN radar data it is evident that plasma irregularities seem to be present throughout the region of enhanced electron density. The patches are observed to be formed in the cusp region due to bursty flux transfer events and are then transported across the polar cap. During the time period of about 10 minutes when a patch drifted through the RISR‐N field of view, the patch seemed to undergo significant deformation in all three spatial dimensions, with density fluctuations of about 10% and spatial variations leading to stretching and tilting of the patch. The findings show that plasma structuring can likely occur within polar cap patches, which support previous suggestions that a patch is highly variable as it drifts across the polar cap, with a faster spread of irregularities throughout the patch as a result.
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 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".