Mineralogy-dependent sulfide oxidation via polysulfide and thiosulfate pathways during weathering of mixed-sulfide bearing mine waste rock
Bibliographic record
Abstract
Tracking the S oxidation pathway in sulfide-bearing mine waste-rock piles is complicated by variations in water content, O2 and Fe3+ concentrations, microbial diversity, mineralogy, the occurrence of a variety of S species associated with incomplete oxidation, and nonlinear coupling between physicochemical processes. Synchrotron-based S K-edge X-ray absorption near edge structure (XANES) spectroscopy facilitates the identification and quantification of S species (i.e., S2−, S22−, S8, S2O32−, and SO42−) in a weathered mine waste-rock pile containing pyrite, sphalerite, galena, pyrrhotite, and chalcopyrite. Mineralogy-dependent polysulfide and thiosulfate pathways both affect the S oxidation within the waste-rock pile. Currently, the polysulfide pathway, with S8 as the intermediate S species, generates high concentrations of dissolved metals (from the rapid oxidation of monosulfides including sphalerite, galena, pyrrhotite, and chalcopyrite). As these monosulfides are depleted, the thiosulfate pathway of pyrite oxidation, including intermediate oxidation products (i.e., S8 and S2O32−), will become the dominant oxidation pathway, resulting in the potential for generation of additional acidic drainage. This information highlights the importance of identifying the sulfide-mineral oxidation reaction pathways when attempting to estimate acid generation potential, and when developing remediation strategies for the storage and management of sulfide-bearing waste rock.
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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) | 0.001 | 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".