Time domain electromagnetic‐induced polarisation: extracting more induced polarisation information from grounded source time domain electromagnetic data
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Electrical induced polarisation surveys are used to detect chargeable materials in the earth. For interpretation of time domain electrical‐induced polarisation data a common procedure is to first invert the direct current data (electric current on time) to recover conductivity and then invert the induced polarisation data (current off‐time) to recover chargeability. This direct current‐induced polarisation inversion procedure assumes that the off time data are free of secondary electromagnetic induction effects. To comply with this, early time data are often discarded or not recorded. For mid‐time data, an electromagnetic decoupling technique, which removes electromagnetic induction in the observations, needs to be implemented. Usually, responses from a half‐space or a layered earth are subtracted. Recent capability in three‐dimensional time domain electromagnetic forward modelling and inversion allows to revisit these procedures. In a Time domain electromagnetic‐induced polarisation survey, a high sampling rate allows early time channels of the electromagnetic data to be recorded. The recovery of chargeability then follows a three‐step workflow: (i) invert early time channel time domain electromagnetic data to recover the three‐dimensional conductivity; (ii) use that conductivity to compute the time domain electromagnetic response at later time channels and subtract this fundamental response from the observations to extract the induced polarisation responses, and (iii) invert the induced polarisation responses to recover a three‐dimensional chargeability. This workflow effectively removes electromagnetic induction effects in the observations and produces better chargeability and conductivity models compared with conventional approaches. In a synthetic example involving a gradient array, we show that the conductivity structure obtained from the early time channel data, which are usually discarded, is superior to that obtained from the steady state direct current voltages. This adds a further reason to collect these electromagnetic data.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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