Sparse magnetic vector inversion in spherical coordinates
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Bibliographic record
Abstract
ABSTRACT Magnetic vector inversion (MVI) has received considerable attention over recent years for processing magnetic field data that are affected by remanent magnetization. However, the magnetization models obtained with current inversion algorithms are generally too smooth to be easily interpreted geologically. To address this, we have reviewed the MVI formulated in a spherical coordinate system. We tackle convergence issues posed by the nonlinear transformation from Cartesian to spherical coordinates by using an iterative sensitivity weighting approach and a scaling of the spherical parameters. The spherical formulation allows us to impose sparsity assumptions on the magnitude and direction of magnetization independently and, as a result, the inversion recovers simpler and more coherent magnetization orientations. The numerical implementation of our algorithm on large-scale problems is facilitated by discretizing the forward problem using tiled octree meshes. All of our results are generated using the open-source SimPEG software. We determine the enhanced capabilities of our algorithm on a large airborne magnetic survey collected over the Kevitsa Ni-Cu-platinum group elements (PGE) deposit. The recovered magnetization direction inside the ultramafic intrusion and in the host stratigraphy is consistent with laboratory measurements and provides evidence for tectonic deformation.
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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 | 0.001 |
| 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 | 0.002 |
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