Modelling the airborne electromagnetic response of a sphere beneath conductive overburden
Bibliographic record
Abstract
Electromagnetic geophysical methods are used in mineral exploration for the ability to detect conductors at depth. In igneous and metamorphic settings, the background half-space is often largely resistive. In such cases, it is important to consider the interaction between the target conductor and any thin, conductive overburden than might exist above the half-space. The overburden is often comprised of glacial tills and clays or the conductive weathering of basement rocks. This situation can be approximated using a discrete conductor model consisting of a “dipping sphere” in a resistive half-space underlying conductive overburden. A semi-analytical solution that considers the first-order interaction of the sphere and overburden has been derived to calculate the electromagnetic response. The simplicity and efficiency of this solution makes it well suited to be implemented when computation time and immediacy of results are desirable. To this end, we have developed a graphical user interface (GUI) based program to model the electromagnetic response of this model. The program is developed using C++ for the electromagnetic computations and python was used to develop the user interface. The program allows users to change the parameters of the survey and target body and quickly view the resulting changes in the shape and decay of the electromagnetic response. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 1:50 PM Presentation Time: 2:15 PM Location: Poster Station 10 Presentation Type: Poster
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".