Precise Ionosphere Modeling Using Regional GPS Network Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. The ionosphere affects the electromagnetic waves that pass through it by inducing an additional transmission time delay. The ionosphere influence has now become the largest error source in GPS positioning and navigation after the turn-off of the Selective Availability (SA). In this paper, methods of 2D grid-based and 3D tomography-based ionospheric modeling are developed based on regional GPS reference networks. Performance analysis was conducted using data from two different regional GPS reference networks. The modeling accuracy of the vertical TEC (VTEC) is at the level of several TECU for 2D ionospheric modeling and about one TECU for 3D tomographic modeling after a comparison to independent ionospheric map data or directly measured ionospsheric TEC values. The data analysis has indicated that the modeling accuracy based on the 3D tomography method is much higher than the 2D grid-based approach.
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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 | 0.000 |
| 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