LA-ICP-MS Mapping of Barren Sandstone from the Proterozoic Athabasca Basin (Canada)—Footprint of U- and REE-Rich Basinal Fluids
Bibliographic record
Abstract
The Proterozoic Athabasca Basin hosts a large number of high-grade, large-tonnage unconformity-related uranium (U) deposits, many of which are also enriched in rare earth elements (REE). The basin also contains hydrothermal REE mineralization unassociated with U. Previous studies postulated that U and REE were derived from either the basin or the basement; however, the exact source of the metals remains ambiguous. This study provides evidence of U- and REE-rich fluids throughout the Athabasca Basin through laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) mapping of barren sandstone distal to mineralized areas. The results indicate that elevated U and REE concentrations mainly occur in the matrix; there are strong positive correlations between U and REE, Th, P and Sr, and moderate positive correlations between U and Zr, Ba, Fe, Al, K and Ca, but the few spots with the highest U are unrelated to these elements. Quantitative evaluation of the element correlations, together with scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) analysis, suggests that most of the elevated U and REE are hosted in aluminum phosphate sulfate (APS) minerals rather than apatite and monazite. As the APS minerals are of diagenetic-hydrothermal origin, the results testify to the presence of U- and REE-rich fluids within the Athabasca Basin. The elevated Th/U ratio (~10) and REE pattern (strong heavy rare earth element (HREE) depletion) are consistent with a model in which large amounts of U and REE (especially HREE) were leached from the sandstone within the Athabasca Basin and contributed to U and REE mineralization near the unconformity between the sedimentary rocks in the basin and underlying basement rocks. This study demonstrates that LA-ICP-MS mapping can be effectively used to evaluate microscale distribution of elements and their mobility in sedimentary rocks to address mineralization related problems.
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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 | 0.000 |
| 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) | 0.009 | 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".