Boundary truncation of magnetotelluric modeling based on multigrid method
Bibliographic record
Abstract
Boundary truncation was applied for homogeneous half-space model and three-layer model based on the multigrid method.Compared to traditional coarse grid approximations,an average weighted method was used to generate the coarse grid approximation and general Fourier analysis was carried out for convergence analysis.Utilizing cycles or component of multi-grid method,the modeling area was reduced to improve modeling efficiency.The numerical results for boundary truncation were compared with numerical results by direct solver.The results show that the weighted average method has a better convergence behavior than Galerkin method and slightly poorer convergence than geometric method.General Fourier analysis is not sensitive to conductivity discontinuities and can not demonstrate the convergence differences caused by the discontinuities.As the truncation increases,deviation from the theoretical results becomes more obvious.When the boundary is truncated to around twice the skin depth,and the results are well approximated with theoretical results.In the log space(or just log frequency),when the truncated boundary value cannot well represent the real value,the calculated absolute electrical field(or phase) tends to move up and down at the same level with respect to frequency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".