A comprehensive study of including structural orientation information in geophysical inversions
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we investigate options for incorporating structural orientation information into under-determined inversions in a deterministic framework (i.e. minimization of an objective function). The first approach involves a rotation of an orthogonal system of smoothness operators, for which there are some important practical details in the implementation that avoid asymmetric inversion results. The second approach relies on addition of linear constraints into the optimization problem, which is solved using a logarithmic barrier method. A 2-D synthetic example is provided involving a synclinal magnetic structure and we invert two sets of real survey data in 3-D (one gravity data, the other magnetic data). Using those examples, we demonstrate how different types of orientation information can be incorporated into inversions. Incorporating orientation information can yield bodies that have expected aspect ratios and axis orientations. Physical property increase or decrease in particular directions can also be obtained.
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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 | 0.001 |
| 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