A wavelet thresholding technique for local geoid and deflection of the vertical determination using a planar approximation
Bibliographic record
Abstract
SUMMARY A computational scheme using the wavelet transform is employed for local geoid determination, where wavelet multiresolution analysis (MRA) is introduced as an alternative approach to the well-established fast Fourier transform (FFT). The Stokes and Vening Meinesz integrals are approximated in finite MRA subspaces. The algorithm is built using an orthogonal wavelet base function. The characteristics of the base function and its effect on the final result are investigated. Hard and soft thresholding are tested in the compression of the kernel as well as global thresholding is compared to level-wise thresholding to optimize the compression level with an acceptable accuracy. Both global and level-wise thresholding are combined in order to achieve the maximum compression level, with acceptable geoid accuracy. The compression rate depends on the degree of singularity of the kernel. In the case of Stokes, a 94 per cent compression level is achieved with 1 cm (rms) accuracy in comparison to FFT and numerical integration approaches. Due to its stronger singularity, in the case of the Vening Meinesz kernel, 97 per cent compression rate is achieved with a 0.07 arc-second (rms) accuracy. The compression percentages achieved in this study are higher than those reported in pervious studies, which shows that this algorithm is very suitable for use in local geoid determination.
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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".