Exploration for unconformity-type uranium deposits with audiomagnetotelluric data: A case study from the McArthur River mine, Saskatchewan, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it