GPS total electron content variations associated with poleward moving Sun‐aligned arcs
Bibliographic record
Abstract
GPS total electron content (TEC) has shown quasiperiodic oscillations of varying amplitude associated with poleward moving Sun‐aligned arcs. The amplitude of TEC variations showed a maximum of ∼3 TECU and seemed to decrease as the arcs moved poleward from the source/generation region. Simultaneous DMSP data showed that fluctuations in TEC and optical intensification were caused by precipitation of high‐energy (>500 eV) particles. Concurrent ionosonde observations also exhibited quasiperiodic variations (within limit of the resolution of the data) in peak ionospheric electron density of the ionosphere. Bottom height of the ionospheric layers produced by precipitating particles varied between 130 km (upper E region) and 300 km (F region), indicating variable particle precipitation energy. Frequency analysis of high‐resolution TEC data showed a broad range of discrete frequency components from 1.60 mHz to 22.80 mHz present in the TEC oscillations, which may provide insight into the energization/modulation of precipitating particles by these oscillations. A broad distribution of equivalent vertical thickness of arcs was calculated using GPS TEC and ionosonde measurements of peak electron density. This distribution showed a minimum thickness of 21 km, a maximum of 84 km, and an average of 49 km. The equivalent vertical thickness also showed a linear relationship with bottomside height of the ionospheric layer (auroral arc). The relationship showed an increase in the vertical thickness with an increase in bottomside height of the layer. This relationship is a consequence of variations in the energy of the precipitating particles causing different ionospheric production profiles.
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 | 0.001 | 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".