Sounding of the Ionosphere Using the CanX-2 Nano-Satellite and Single-Frequency Radio Occultation Techniques
Bibliographic record
Abstract
The objective of the research presented in this thesis is to show that single-frequency ionospheric electron density profiles can be obtained using GPS radio occultation techniques with commercial, off-the-shelf hardware. The platform used in support of this objective is the CanX-2 nanosatellite. Limitations with respect to the antenna’s field of view and poor signal quality are overcome with the use of the code-minus-carrier observable, TEC calibration and a various smoothing techniques. All techniques are validated through comparison of the corresponding vertical electron density profiles to optimized data assumed to be the best possible representations of the true ionospheric signal. This assumption is substantiated through application of the optimization procedure to raw COSMIC data and comparison to COSMIC published post-processed product. Smoothing of raw CanX-2 code-minus-carrier data was conducted via polynomial fit and a moving-average filter. Both methods fared very well when compared to the optimized data. The radio occultation research performed with CanX-2 represents 2 orders of magnitude decrease in cost over similar work conducted by larger-budget and larger-scope programs.
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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) | 0.002 | 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".