UNIVERSITY OF CALGARY Evaluation of 2-Dimensional Ionosphere Models for National And Regional GPS Networks in Canada
Bibliographic record
Abstract
The purpose of this research is to determine a 2-dimensional ionosphere model, applicable in real-time, that provides optimal accuracy of vertical delays at ionospheric grid points (IGPs). This model is based on GPS delays measured at ionospheric pierce points (IPPs), as observed from dual-frequency GPS tracking stations. Two algorithms are selected for possible implementation: spherical harmonic model and thin plate spline interpolation. These methods are based on two-dimensional estimation on an ionospheric shell at 350 km altitude. The input observations are computed as slant delays using dual frequency GPS observations. In the spherical harmonics model, the coefficients and receiver differential code biases are estimated every 5 minutes in a real-time mode using a Kalman filter. Thin-plate spline is a 2-dimensional generalization of the cubic spline in 1 dimension. The basic idea of this method is to build a function that passes through the grid points and minimizes the roughness of the surface. The performance of the two algorithms is evaluated in terms of accuracy of the residuals between observed vertical TECs (VTECs) and estimated VTECs at IGPs in two GPS networks: Canadian Active Control System (CACS) and Western Canada Deformation Array (WCDA). The evaluation results show that the thin plate spline outperforms the spherical harmonics model in both networks. The spatial and temporal variation of the geomagnetic storm is also investigated by plotting vertical TEC maps over Canada. In considering the VTEC maps generated for the storm period, it is observed that regions with large enhancements of vertical TEC coincide well with the locations of stations with larger rms values. iii
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".