Tracing Molybdenum Attenuation in Mining Environments Using Molybdenum Stable Isotopes
Bibliographic record
Abstract
Molybdenum contamination is a concern in mining regions worldwide. Better understanding of processes controlling Mo mobility in mine wastes is critical for assessing potential impacts and developing water-quality management strategies associated with this element. Here, we used Mo stable isotope (δ98/95Mo) analyses to investigate geochemical controls on Mo mobility within a tailings management facility (TMF) featuring oxic and anoxic environments. These isotopic analyses were integrated with X-ray absorption spectroscopy, X-ray diffraction, Raman spectroscopy, transmission electron microscopy, and aqueous chemical data. Dissolved Mo concentrations were inversely correlated with δ98/95Mo values such that enrichment of heavy Mo isotopes in solution reflected attenuation processes. Inner-sphere complexation of Mo(VI) with ferrihydrite was the primary driver of Mo removal and was accompanied by a ca. 1‰ isotope fractionation. Limited Mo attenuation and isotope fractionation were observed in Fe(II)- and Mo-rich anoxic TMF seepage, while attenuation and isotope fractionation were greatest during discharge and oxidation of this seepage after discharge into a pond where Fe-(oxyhydr)oxide precipitation promoted Mo sorption. Overall, this study highlights the role of sorption onto Fe-(oxyhydr)oxides in attenuating Mo in oxic environments, a process which can be traced by Mo isotope analyses.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".