Conductance estimates from spatial and temporal derivatives of borehole electromagnetic data
Bibliographic record
Abstract
The conductance of an infinite uniformly conductive thin sheet can be calculated using the ratio of the temporal gradient and the gradient in the normal direction of any component (or combination of components) of the secondary magnetic field. With standard borehole electromagnetic (BHEM) systems, both gradients can be readily calculated using finite difference approximations. For a finite thin sheet, synthetic modeling demonstrated that the magnitude of the field provided a robust and reliable apparent conductance in typical 3-component BHEM survey configurations. In a field example of BHEM data collected over a massive sulfide deposit in Sudbury, Ontario, Canada, the spatial gradient could be calculated over a roughly 100 m wide zone and a consistent apparent conductance could be calculated at each delay time using the magnitude of the field. Increases in the apparent conductance estimate with increasing delay time are likely due to currents migrating into more conductive parts of the body. The apparent conductance values are also consistent with Maxwell models. This simple and robust apparent conductance is ideal as a first pass estimate for target discrimination, grade estimation and starting values for modeling and inversion.
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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 | 0.003 |
| 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 | 0.001 |
| 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".