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Natural Attenuation Reactions at a Uranium Mill Tailings Site, Western U.S.A.

2002· article· en· W1971742956 on OpenAlexaff
Chen Zhu, G. M. Anderson, David S. Burden

Bibliographic record

VenueGround Water · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTailingsPlumeAquiferUraniumGroundwaterGeologyGeochemical modelingCalciteEnvironmental chemistryMineralogyChemistryGeotechnical engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.006

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.

Opus teacher head0.012
GPT teacher head0.212
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2002
Admission routes1
Has abstractyes

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