Theta map: Edge detection in magnetic data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The 3D analytic signal amplitude of a total magnetic intensity (TMI) map, introduced by Roest et al. (1992), is widely used in magnetic interpretation as a means of positioning anomalies directly over their sources. This technique is most important at low magnetic latitudes, where reduction to the pole distorts anomalies to the point where they often become uninterpretable: the reduction operator does not converge if the magnetization and regional field are truly horizontal (Baranov, 1957). Methods have been devised to suppress the artifacts appearing in low-latitude reduction to the pole, but no method can reduce such data without distortion (e.g., Silva, 1986; Hansen and Pawlowski, 1989), which becomes severe for inclinations less than 20°. The amplitude of the analytic signal, denoted by |A|, has the added advantage of being independent of the orientation of magnetization of the source bodies. It reaches a maximum over magnetic contacts, and thus, in theory, can be used to trace the outline of magnetic bodies. In practice, especially in the case of aeromagnetic data at high instrument-source separation, |A| is high over magnetic bodies, but is not sufficient to resolve body edges. This appears to be true even with higher-order analytic signal derivatives (Debeglia and Corpel, 1997, their Figure 11).
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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 | 0.000 |
| 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) | 0.001 | 0.003 |
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