Analysis of the Mo Speciation in the JEB Tailings Management Facility at McClean Lake, Saskatchewan
Bibliographic record
Abstract
The JEB Tailings Management Facility (TMF) is central to reducing the environmental impact of the uranium ore processing operation located at the McClean Lake facility and operated by AREVA Resources Canada (AREVA). The geochemical controls of this facility are largely designed around the idea that elements of concern, such as Mo, will be controlled in the very long term through equilibrium with supporting minerals. However, these systems are far from equilibrium when the tailings are first placed in the TMF, and it can take years, decades, or centuries to reach equilibrium. Therefore, it is necessary to understand how these reactions evolve toward an equilibrium state to understand the very long-term behavior of the TMF and to ensure that the elements of concern will be adequately contained. To this end, the Mo speciation in a series of samples taken from the JEB TMF during the 2008 sampling campaign has been analyzed. This analysis was performed using powder X-ray diffraction (XRD), X-ray fluorescence mapping (μ-XRF), and X-ray absorption near-edge spectroscopy (XANES). These results show that only XANES was effective in speciating Mo in the tailings samples, because it was both element-specific and sensitive enough to detect the low concentrations of Mo present. These results show that the predominant Mo-bearing phases present in the TMF are powellite, ferrimolybdite, and molybdate adsorbed on ferrihydrite.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".