Troposphere Modeling in a Regional GPS Network
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. By using a regional network of Global Positioning System (GPS) reference stations, it is possible to recover estimates of the slant wet delay (SWD) to all GPS satellites in view. SWD observations can then be used to model the vertical and horizontal structure of water vapor over a local area, using a tomographic approach. The University of Calgary currently operates a regional GPS real-time network of 14 sites in southern Alberta. This network provides an excellent opportunity to study severe weather conditions (e.g. thunderstorms, hail, and tornados) which develop in the foothills of the Rockies near Calgary. In this paper, a 4-D tomographic water vapor model is tested using the regional GPS network. A field campaign was conducted during July 2003 to derive an extensive set of truth data from radiosonde soundings. Accuracies of tomographic water vapor retrieval techniques are evaluated for 1) using only ground-based GPS input, and 2) using a ground-based GPS solution augmented with vertical wet refractivity profiles derived from radiosondes released within the GPS network. Zenith wet delays (ZWD) are computed for both cases, by integrating through the 4-D tomography predictions, and these values are compared with truth ZWD derived from independent radiosonde measurements. Results indicate that ZWD may be modeled with accuracies at the sub-centimeter level using a ground-based GPS network augmented with vertical profile information. This represents an improvement over the GPS-only 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 | 0.000 |
| 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 it