The South American gravimetric quasi-geoid: QGEOID2021
Bibliographic record
Abstract
The South American gravimetric quasi-geoid model, named QGEOID2021, was computed thanks to a collaboration of several institutions, companies and universities of South America. The model covers the area between 15°N and 60°S in latitude and 100°W and 30°W in longitude, with a grid resolution of 5' x 5'. It is based on 959,404 terrestrial gravimetric points, the XGM2019 global geopotential model up to degree and order 200 and the SRTMv3 digital terrain model. The short wavelengths of the solution were estimated via Fast Fourier Transform (FFT) with the modified Stokes kernel proposed by Vaníček and Kleusberg (1987). On the other hand, long and medium wavelengths were removed and replaced in the framework of a remove-compute-restore procedure. Regions without gravimetric observations were completed using XGM2019 to its full degree. The calculation of the geoid model was performed by the Canadian package SHGEO (Stokes-Helmert Geoid Software). The quasi-geoid model was obtained by the classical geoid/quasi-geoid separation term (Heiskanen and Moritz, 1967). The comparison between height anomalies and GPS/levelling data at 1108 points in Brazil shows differences with an RMS of 41 cm. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.010 |
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".