Comparison of IGS and Radiosonde Determination of ZTD in the Canadian Arctic
Bibliographic record
Abstract
Zenith Total Delay (ZTD) induced by the neutral atmosphere on GPS signals is a source of information for Numerical Weather Prediction (NWP) models and climate studies. Currently, the International GNSS Service (IGS) provides two types of tropospheric (neutral atmosphere) zenith path delay products: the Ultra-Rapid product with a latency of 2-3 hours and the final product with a latency of less than 4 weeks. The final IGS ZTD products are among the most accurate GPS ZTD products as they are derived from the results of all of the IGS processing centers. Although (due to the time latency) the final products may not be of use in NWP models’ data assimilation, they can be valuable data for climate studies. Furthermore, time series analysis of the GPS ZTD data may be used for spatial and temporal correlation studies. Approximately 34 months of GPS and radiosonde ZTD results for stations in and around the Canadian Arctic are compared. The results show an overall bias of 4.7 mm (GPS-RAOB) and a standard deviation of 5.8 mm which are comparable with studies carried out in other parts of the world. Long term analysis of differenced time series might help to model the error characteristic of the derived ZTD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".