Recovery of 3D IP distribution from airborne time-domain EM
Bibliographic record
Abstract
Conventional IP is not the only technique that is sensitive to chargeable material. Any electromagnetic method applied in the presence of chargeable material will be affected. Unfortunately, the effects are often hard to recognize in the data. For the particular case of coincident loop time-domain EM data, negative transients - soundings with a reversal in sign of the received fields - are diagnostic of chargeable materials. This property can also be extended to center loop systems, including many airborne systems. Negative transients are commonly observed in airborne TEM systems, such as Fugro’s AeroTEM system or Geotech’s VTEM system.We develop an inversion methodology to attempt to recover a three dimensional distribution of chargeability from observations of negative transients in airborne time- domain electromagnetic data. Forward modeling of chargeable targets is performed directly in the time domain, and the sensitivity of these data to the presence of chargeable material is derived. The methodology is applied to a synthetic data set. Areas of future work and potential problems are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".