Geochemical Controls on Uranium Release from Neutral-pH Rock Drainage Produced by Weathering of Granite, Gneiss, and Schist
Bibliographic record
Abstract
We investigated geochemical processes controlling uranium release in neutral-pH (pH ≥ 6) rock drainage (NRD) at a prospective gold deposit hosted in granite, schist, and gneiss. Although uranium is not an economic target at this deposit, it is present in the host rock at a median abundance of 3.7 µg/g, i.e., above the average uranium content of the Earth’s crust. Field bin and column waste-rock weathering experiments using gneiss and schist mine waste rock produced circumneutral-pH (7.6 to 8.4) and high-alkalinity (41 to 499 mg/L as CaCO3) drainage, while granite produced drainage with lower pH (pH 4.7 to >8) and lower alkalinity (<10 to 210 mg/L as CaCO3). In all instances, U release was associated with calcium release and formation of weakly sorbing calcium-carbonato-uranyl aqueous complexes. This process accounted for the higher release of uranium from carbonate-bearing gneiss and schist than from granite despite the latter’s higher solid-phase uranium content. In addition, unweathered carbonate-bearing rocks having a higher sulfide-mineral content released more uranium than their oxidized counterparts because sulfuric acid produced during sulfide-mineral oxidation promoted dissolution of carbonate minerals, release of calcium, and formation of calcium-carbonato-uranyl aqueous complexes. Substantial uranium attenuation occurred during a sequencing experiment involving application of uranium-rich gneiss drainage into columns containing Fe-oxide rich schist. Geochemical modeling indicated that uranium attenuation in the sequencing experiment could be explained through surface complexation and that this process is highly sensitive to dissolved calcium concentrations and pCO2 under NRD conditions.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".