3D Airborne EM Forward Modelling by the Spectral-Element Method for Deformed Hexahedral Meshes
Bibliographic record
Abstract
Summary Accuracy and efficiency of forward modelling is important for successful and practical inversion and interpretation of airborne EM data. Finite-difference and finite-element methods are currently the most common methods used. However, an alternative approach is the spectral-element (SE) method, which is attractive because of its flexibility and potential for high accuracy. The SE method has previously been implemented for airborne EM modeling using regular hexahedral meshes. Here, we implement the SE method for deformed hexahedral meshes. This enables complex geological bodies to be modelled. A shape function is used to calculate the Jacobian matrix of the mapping between the physical mesh coordinates and the reference coordinates for the SE method. We apply our SE method to the computation of frequency-domain airborne EM responses. Through some numerical examples with rough mesh subdivision and simple mesh deformation, we demonstrate the flexibility and accuracy of the SE method for computing frequency-domain airborne EM responses, —thus verifying the potential of SE method for modeling complex geological bodies.
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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 | 0.000 |
| 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".