Multifrequency Scintillation in the Polar Caps
Bibliographic record
Abstract
In the ionosphere, plasma density structures with scales sizes ranging from a few centimeters to hundreds of kilometers are capable of modifying the phase and amplitude of a radio signal in a rapid random manner in a process called scintillation. The Coherent Electromagnetic Radio Tomography (CERTO) and the Canadian High Arctic Ionospheric Network (CHAIN) are two different networks of scintillation receivers, each with a station in Resolute Bay, Canada. CERTO measures amplitude and phase signals in VHF and UHF while CHAIN measures amplitude and phase signals in the L-band. Through these measurements we can calculate the scintillation indexes, S_4 and sigma_phi to gain insight into the plasma density structures the scintillation originated from. In this Thesis, the processes of detrending and processing VHF sigma_phi from CERTO data and L-band S_4 & sigma_phi CHAIN data are detailed and the resulting scintillation data are analyzed by comparing the time of events to data from the Resolute Bay Incoherent Scatter Radar (RISR), creating histograms of the total scintillation data acquired, and by examining CERTO sigma_phi data results with respect to elevation angle. This work concludes that detrending scintillation data at frequencies other than L-band is not a trivial process and must be given care in order to produce accurate results. Within this work none of the RISR data contained significant plasma density during any of the satellite conjunctions analyzed. The histograms of total VHF and L-band sigma_phi values show more variation in the average VHF sigma_phi values than in the L-band sigma_phi. A positive correlation between the satellites elevation angle and increase in sigma_phi is identified.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".