The GGXF Standard File Format for Gridded Geodetic Data
Bibliographic record
Abstract
Abstract Monitoring the Earth is undertaken in numerous geometric and physical reference frames and coordinate reference systems. Analysis often requires transformation of coordinates between these frames. As the accuracy of positioning and geospatial data improves, the use of gridded data to describe the quantities used in these coordinate transformations is increasing. Rectangular grids also provide an efficient means of disseminating other geodetic data. IAG Commission 1 Working Group 1.3.1 in association with the Open Geospatial Consortium (OGC) have developed a Geodetic data Grid eXchange Format (GGXF) for quantifying and disseminating gridded geodetic data. GGXF was developed in conjunction with a functional model for crustal deformation (FMCD) including support for time-dependent changes, but has been designed to support any type of regularly-gridded geodetic data including but not limited to geoid models, offsets between reference frames (of one, two or three dimensions), velocity grids, tidal surfaces, etc. The purpose of GGXF is to provide a single comprehensive, efficient distribution format through which producers can disseminate gridded geodetic data and users can exchange and apply this information. This paper presents an overview of the GGXF format.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.158 | 0.181 |
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".