The North America Reference Frame (NAREF) Project to Densify the ITRF in North America
Bibliographic record
Abstract
Since the beginning of 2001, the Geodetic Survey Division of Natural Resources Canada (NRCan) has been playing a leading role in the North American Reference Frame (NAREF) Working Group of IAG Subcommission 1.3c (Regional Reference Frames for North America) in support of the International Earth Rotation and Reference Frames Service (IERS) and International GNSS Service (IGS) initiatives to densify the International Terrestrial Reference Frame (ITRF) in North America. The goal is to provide a consistent reference frame, including velocity models, procedures and transformations, tied to ITRF in which scientific and geomatics results (e.g., positions in tectonically active areas) can be produced and compared. The NAREF densification network has evolved from a hundred continuously operating GPS reference stations to nearly 1000. Several groups in Canada and the U.S. provide weekly coordinate solutions which are combined together in an official NAREF solution that is aligned with the ITRF reference frame of date. These combination solutions are available to the public via the IGS archives with a latency of about 4 weeks. In addition, we have also begun to estimate annual velocity solutions based on the weekly coordinate solutions. The first of these was contributed to the ITRF2005 densification effort currently underway. The resulting velocity field has been used to evaluate crustal deformations in various parts of the continent and to more accurately determine the motion of stable North America. The previous version has been used to define a plate-fixed Stable North American Reference Frame (SNARF) for the Plate Boundary Observatory component of the EarthScope project. This new, high accuracy reference frame may eventually supersede NAD83. Based on six years of experience, we discuss several factors that affect the quality of our solutions, including monumentation, equipment changes and various kinds of biases and noise. We also describe changes in our processing and combination strategies in response to new procedures adopted by the IGS. Finally, future plans for reprocessing all solutions will be presented.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".