Molybdenum Speciation in Uranium Mine Tailings Using X-Ray Absorption Spectroscopy
Bibliographic record
Abstract
Uranium (U) mill tailings in northern Saskatchewan, Canada, contain elevated concentrations of molybdenum (Mo). The potential for long-term (>10,000 years) mobilization of Mo from the tailings management facilities to regional groundwater systems is an environmental concern. To assist in characterizing long-term stability, X-ray absorption spectroscopy was used to define the chemical (redox and molecular) speciation of Mo in tailings samples from the Deilmann Tailings Management Facility (DTMF) at the Key Lake operations of Cameco Corporation. Comparison of Mo K near-edge X-ray absorption spectra of tailings samples and reference compounds of known oxidation states indicates Mo exists mainly as molybdate (+6 oxidation state). Principal component analysis of tailings samples spectra followed by linear combination fitting using spectra of reference compounds indicates that various proportions of NiMoO(4) and CaMoO(4) complexes, as well as molybdate adsorbed onto ferrihydrite, are the Mo species present in the U mine tailings. Tailings samples with low Fe/Mo (<708) and high Ni/Mo (>113) molar ratios are dominated by NiMoO(4), whereas those with high Fe/Mo (>708) and low Ni/Mo (<113) molar ratios are dominated by molybdate adsorbed onto ferrihydrite. This suggests that the speciation of Mo in the tailings is dependent in part on the chemistry of the original ore.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".