Exploration for unconformity-type uranium deposits with audiomagnetotelluric data: A case study from the McArthur River mine, Saskatchewan, Canada
Bibliographic record
Abstract
Abstract Unconformity-type deposits supply a significant amount of the world's uranium and consist of uranium that is generally codeposited with graphite in a fault zone. The low resistivity of the graphite produces a significant contrast in electrical resistivity, which can be located with electromagnetic (EM) methods. The Athabasca Basin in Western Canada hosts significant uranium deposits, and exploration in deeper parts of the basin has required the application of new EM methods. This paper presents an evaluation of the audiomagnetotelluric (AMT) exploration method at the McArthur River mine in the Athabasca Basin. AMT data were collected at 132 stations on a grid, and two-dimensional (2D) and three-dimensional (3D) inversions were used to generate resistivity models. These models showed two major results: (1) a significant conductor coincident with a major basement fault (P2) and the uranium deposits (this conductor begins at the unconformity at a depth of 550 m and extends to a depth of at least three km) and (2) a resistive halo which might be caused by the silicification associated with mineralization. However, synthetic inversions showed that this halo could be an artifact of smoothing function in the inversion scheme. The 2D inversions were validated by synthetic inversions, comparison with the 3D inversion models, and correlation with well-log information. 3D AMT forward modeling showed that strong 3D effects are not present in the AMT impedance data. Induction vectors showed more evidence of complexity, but the inclusion of these data in the inversion improved subsurface resolution.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".