Mineralogical Characterization of Arsenic in Uranium Mine Tailings Precipitated from Iron-Rich Hydrometallurgical Solutions
Bibliographic record
Abstract
Arsenic-rich uranium mine tailings from the Rabbit Lake in-pit tailings management facility (RLITMF) in northern Saskatchewan, Canada, were investigated to determine the mineralogy and long-term stability of secondary arsenic precipitates formed from iron-rich hydrometallurgical solutions. Total arsenic and iron concentrations in six iron-rich samples of the mine tailings ranged from 56 to 6,000 microg/g and from 12 600 to 30 200 microg/g, respectively (Fe/As molar ratios of 5.3-303). On the basis of stability field diagrams generated from pH, Eh, and temperature measurements on tailings samples (mean values of 9.79, +162 mV, and 2.8 degrees C, respectively), it was concluded that arsenic and iron in the tailings were stable as As5+ and Fe3+. Synchrotron-based X-ray absorption spectroscopic studies of tailings samples, fresh mill precipitates, and reference compounds showed that the arsenic in iron-rich areas of the tailings existed as the stable As5+ and was adsorbed to 2-line ferrihydrite through inner-sphere bidentate linkages. Furthermore, under the conditions in the RLITMF, the 2-line ferrihydrite did not undergo any measurable conversion to more crystalline goethite or hematite, even in tailings discharged to the RLITMF 10 yr prior to sampling.
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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 | 0.000 | 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) | 0.000 | 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 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".