Polar cap patches, GPS TEC variations, and atmospheric gravity waves
Bibliographic record
Abstract
The southward pointing field of view of the Canadian component of the Resolute Bay Incoherent Scatter Radar (RISR-C) is well suited for observing the ionospheric signatures of flux transfer events and subsequent polar patch formation in the cusp. The fast azimuthally oriented flows and associated density depletions often show an enhanced ion temperature from Joule heating caused by the sudden change in plasma flow direction. The newly formed polar patches are then observed as they propagate through the field-of-views of both RISR-C and RISR-N. In the ionosphere, the electron density gradients imposed in the cusp, and small-scale irregularities resulting from gradient-drift instability, particularly in the trailing edges of patches, cause GPS TEC and phase variations, and sometimes amplitude scintillation. The neutral atmosphere is affected by ionospheric currents resulting in Joule heating. The pulses of ionospheric currents in the cusp launch atmospheric gravity waves (AGWs) causing traveling ionospheric disturbances, as they propagate equatorward and upward. On the other hand, the downward propagating AGW packets can impact the lower atmosphere, including the troposphere. Despite significantly reduced wave amplitudes, but subject to amplification upon over-reflection in the upper troposphere, these AGWs can trigger/release existing moist instabilities, initiating convection and latent heat release, the energy leading to intensification of storms.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".