High-Precision Ionospheric TEC Recovery Using a Regional-Area GPS Network
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Bibliographic record
Abstract
ABSTRACT: A new method of ionospheric total electron content (TEC) recovery has been developed and is described in this paper. It focuses on recovering ionospheric vertical TEC at centimeter accuracy using carrier phase as the principal observable from regional-area GPS networks. To eliminate satellite- and receiver-dependent biases, the double-difference technique is applied to derive reference network ionospheric measurements. A grid model with a moving window is used along with a streamlined Kalman filter to model and estimate the absolute vertical ionospheric TEC across the GPS network. Numerical tests have been carried out to assess the attainable accuracy of the ionosphere estimates using data from an operational GPS network. The results confirm that regional ionospheric TEC estimates can be determined at an accuracy of several centimeters.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it