Multicomponent reactive transport modeling of acid neutralization reactions in mine tailings
Bibliographic record
Abstract
Multicomponent reactive transport modeling was conducted to analyze and quantify the acid neutralization reactions observed in a column experiment. Experimental results and the experimental procedures have been previously published. The pore water geochemistry was described by dissolution and precipitation reactions involving primary and secondary mineral phases. The initial amounts of the primary phases ankerite‐dolomite, siderite, chlorite, and gypsum were constrained by mineralogical analyses of the tailings sample used in the experiment. Secondary gibbsite was incorporated into the model to adequately explain the changes in pH and concentration changes of Al in the column effluent water. The results of the reactive transport modeling show that the pH of the column effluent water can be explained by dissolution reactions of ankerite‐dolomite, siderite, chlorite, and secondary gibbsite. The modeling results also show that changes in Eh can be explained by dissolution of ferrihydrite during the experiment. In addition, the modeling results show that the kinetically limited dissolution of chlorite contributes the largest mass of dissolved Mg and Fe (II) in the effluent water, followed by ankerite‐dolomite, which contributes substantially less. In summary, reactive transport modeling based on detailed geochemical and mineralogical data was successful to quantitatively describe the changes in pH and major ions in the column effluent.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".