Nonlinear anisotropic diffusive filtering applied to the ocean's mean dynamic topography
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Bibliographic record
Abstract
Despite the improvement in global geoid determination that the Gravity Recovery and Climate Experiment (GRACE) satellite mission has provided, it remains necessary to filter the ocean's mean dynamic topography (MDT) that is derived from it to remove residual noise. A standard approach is to use isotropic spatial smoothing. Unfortunately, this also attenuates MDT gradients associated with surface currents. Here an alternative, anisotropic approach taken from the field of image processing that preferentially filters along rather than across gradients is presented. Applying the method to the MDT of the North Atlantic, it is found that attenuation of MDT gradients corresponding to important currents such as the Gulf Stream and Labrador Current is much reduced. Along the axis of the Gulf Stream, this translates in places to more than a doubling in the estimated current speed compared to a conventionally filtered MDT.
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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 it