Spectral Analysis of Gravity Field Data and Errors in view of Sub-Decimetre Geoid Determination in Canada
Bibliographic record
Abstract
Recent developments in the modern geodetic, geophysics and oceanographic applications require a geoid with absolute accuracy of 10 centimetre or better and a relative accuracy of 1 part per million (ppm) of the inter-station distance. Gravity field data in Canada are spectrally analysed with the view of refining geoid estimation methods that will yield the above-mentioned accuracy requirements. The analysis is based on estimates of empirical covariance functions and degree variances derived from local gravity observations, a global geopotential model (EGM96), and topographic heights. Numerical results for selected areas in mountainous, flat and marine areas of Canada show that the empirical signal and error covariance functions are non-uniform and they are highly correlated with the roughness of the topography. Gravity data and topographic heights with 1 spatial resolution are required for 1 cm geoid in the mountainous areas while the same level of geoid accuracy can be achieved with ...
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".