Natural Attenuation Reactions at a Uranium Mill Tailings Site, Western U.S.A.
Bibliographic record
Abstract
This paper presents a modeling analysis of the geochemical evolution of a contaminated sandy aquifer at a uranium mill tailings site in the western United States. The tailings pond contains fluids having a pH of 1.5 to 3.5 and high levels of As, Be, Cd, Cr, Pb, Mo, Ni, Se, 226Ra, 228Ra, 230Th, 238U, and 234U. Seepage of tailings fluids into the aquifer has formed a low-pH ground water plume. The reclamation plan is to install a low-permeability cover on the tailings pond to stop the seepage and allow the plume to be attenuated by reactions with the aquifer matrix and flushed by uncontaminated upgradient ground water. To evaluate this reclamation scenario, ground water and sediment core samples were analyzed along one flowpath. Speciation-solubility and mass-transfer modeling revealed two sets of chemical reactions for acid seepage and flushing, respectively. The current concentrations and distribution of ground water constituents can be interpreted as being controlled by stepwise pH-buffer reactions with calcite, amorphous aluminum hydroxide, and amorphous iron hydroxides. These buffer reactions divide the aquifer into zones of near-constant pH, separated by interface zones. For the flushing stage, it is predicted that reactions with surface-bound species will dominate the reaction paths, and more pore volumes are required to neutralize the plume than predicted by models that do not consider surface reactions. Direct mineralogical and surface analysis is needed to substantiate this assertion.
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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 | 0.001 | 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".