Mapping of the resistivity, susceptibility, and permittivity of the earth using a helicopter-borne electromagnetic system
Bibliographic record
Abstract
Abstract Interpretation of helicopter-borne electromagnetic (EM) data is commonly based on the mapping of resistivity (or conductivity) under the assumption that the magnetic permeability is that of free space and dielectric permittivity can be ignored. However, the data obtained from a multifrequency EM system may contain information about the magnetic permeability and dielectric permittivity as well as the conductivity. Our previous work has shown how helicopter EM data may be transformed to yield the resistivity and magnetic permeability or, alternatively, the resistivity and dielectric permittivity. A method has now been developed to recover the resistivity, magnetic permeability, and dielectric permittivity together from the transformation of helicopter EM data based on a half-space model. A field example is presented from an area which exhibits both permeable and dielectric properties. This example shows that the mapping of resistivity, magnetic permeability, and dielectric permittivity together yields more credible results than if the permeability or permittivity is ignored.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".