Induced-polarization effects in airborne electromagnetic data: Estimating chargeability from shape reversals
Bibliographic record
Abstract
Induced polarization effects have been seen since the 1970s in ground EM data and in airborne EM data since the 1990s. These effects normally manifest themselves as negative amplitudes in transient electromagnetic data. For fixed-wing towed-bird electromagnetic systems, negatives can also occur as a geometric effect, but for systems where the transmitter is effectively coincident with the receiver, Weidelt has shown that coincident-system negatives can only be explained as an induced polarization effect. These negatives are now being seen more frequently in airborne data as the systems have become more powerful and fly closer to the ground. Previous studies showed that the negatives are largest and most evident when the current induced in the ground is strong, but decays away quickly and the ground has a significant chargeability. These conditions have been satisfied in permafrost conditions, over lakes, over kimberlites, and near to disseminated mineralization. Identifying induced polarization effects where negatives do not occur is challenging: it can be done by analyzing the decay rate, or as I describe in this paper by looking at reversals in the shape of the response in combination with the decay rate. Presentation Date: Wednesday, October 19, 2016 Start Time: 1:30:00 PM Location: Lobby D/C Presentation Type: POSTER
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How this classification was reachedexpand
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 | 0.002 |
| 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) | 0.002 | 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 teacher head, 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".