Modelling IP effects in airborne time domain electromagnetics
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
The presence of chargeable materials can significantly impact the data in electromagnetic (EM) surveys. This affected data has traditionally been treated as noise that must be removed prior to interpretation or inversion. The ability to extract induced polarization (IP) information from an airborne platform would be a valuable tool in the mineral exploration industry, and thus the pursuit of this ability has recently led to significant interest in the interpretation of IP effects in airborne data. A variety of interpretation methodologies have been proposed to aid in the identification and extraction of information from time domain EM data containing IP effects. Any interpretation scheme needs to be thoroughly tested on realistic synthetic examples so that the strengths and weaknesses of the method are well understood.In this work, we present a methodology for accurately and efficiently simulating the response of a time domain EM experiment by modelling the convolution that occurs in Ohm’s Law in the presence of a frequency dependent conductivity. This method is free of any assumptions about the dimensionality or frequency dependence of the chargeable material and can be used to simulate the response of any time domain system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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