Evaluating Euler pole parameters for the north American terrestrial reference frame of 2022
Bibliographic record
Abstract
Euler Pole Parameters (EPPs) were estimated for the new plate-fixed North American Terrestrial Reference Frame of 2022 (NATRF2022) based on the spherical model of Earth using different sets of continuously operating GPS (cGPS) station velocities. Two objectives were considered in this research: (1) the possibility of using the cGPS stations located in the areas affected by the Glacial Isostatic Adjustment (GIA), and (2) minimizing the reference frame velocities across the entire continent for conventional uses such as surveying and mapping. A key consideration in this analysis is accounting for the impact of the ongoing GIA on the horizontal velocities. The predicted horizontal velocities from the ICE-6G model were used to remove the GIA effect from the velocity field to mitigate such biases. As a proof of concept, different data sets from a large set of cGPS station velocities were selected, and EPPs were estimated for all these sets of stations with and without removing the GIA effect and estimating or not estimating the Plate Translation Rate (PTR). Considering the WRMS as the criterion for showing goodness of fit, the results show that accounting for the GIA effect reduces the NATRF2022 velocities. Using the same velocity dataset, the PTR was estimated along with the conventional Euler's rotation parameters, and it was shown that estimating the PTR term can further reduce the NATRF2022 velocities.
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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".