A model study on enhancing the horizontal gradient of potential fields with the vertical derivative
Bibliographic record
Abstract
The total horizontal gradient (THG) and its derivatives are commonly used in interpreting potential fields. Because THG is a nonharmonic function, its vertical derivative (VD) can be consistently computed using, e.g., a finite-difference approximation. The calculation of VD in the wavenumber domain is physically meaningful for harmonic functions, but it provides a pseudovertical derivative (PVD) when applied to nonharmonic fields that can be used in some edge detectors, such as THG. Through experiments with synthetic and field datasets, we evaluated the performance of the PVD of THG in the tilt angle of THG (TAHG) and fast sigmoid-based edge detector (FSED). TAHG and FSED are known as THG-based filters in mapping the edges of causative bodies. The results with synthetic data and magnetic data from the Montresor Belt (Canada) show that maps produced from the PVD of THG are clearer than those from the VD of THG near the source edges. Overall, the PVD of THG significantly enhances the edge detection of potential fields.
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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".