Determination of position coordinates of the new active CORS in Ghana
Bibliographic record
Abstract
Global Navigation Satellite System (GNSS) technologies provide services and applications in a wide range of areas, including survey and mapping, transportation, precision agriculture, urban planning, smart mobility and smart city management, to name a few. Most of these applications rely on real-time kinematic (RTK) technology, which is typically supported by a network of continuously operating reference stations (CORS). In order to improve GNSS applications in Ghana, eight new CORS were established by the Licensed Surveyors Association of Ghana (LiSAG) in 2019 known as LiSAGNet. Accurate and precise positions of the LiSAGNet are, however, very critical for GNSS applications. Thus, the aim of this study is to determine accurate three-dimensional (3D) coordinates of the LiSAGNet using Network-based and Precise Point Positioning (PPP) techniques based on the International Terrestrial Reference Frame (ITRF). Positions of the new CORS were computed from data for 11 consecutive days using gLAB software v5.4.1 in PPP mode and the Canadian Spatial Reference System PPP (CSRS-PPP) online services as a check. Position solutions from both gLAB and CSRS-PPP were compared, which yielded coordinates variability of 0.001 m, 0.003 m and 0.029 m in the northings (N), eastings (E) and up (U) directions respectively and were therefore accepted as the final coordinates of the LiSAGNet. Positions from the PPP and Network-based techniques were also compared to determine consistencies or otherwise in the coordinates of the LiSAGNet. The study concluded that positions of LiSAGNet showed more consistency when determined by Network-based technique than when determined by PPP technique.
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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".