Mineralogical controls on acid-mine drainage from waste piles in the Vermont copper belt
Bibliographic record
Abstract
,Secondary Fe phases, which could attenuate Cu, Zn, and Ni, formed in samples of unacidified filtered surface and ground water from two deposits of sulfide mine tailings at Thompson and Leaf Rapids, Manitoba. The precipitates were separated from the solutions by filtration, and analyzed by XRD, SEM and EMPA. Phases of different crystallinity were separated by selective dissolution with 0.2 M ammonium oxalate solution at pH 3. An assemblage of goethite and schwertmannite precipitated from initially anoxic ground water with a pH of 5.7-6.2, whereas jarosite and/or schwertmannite were identified in acidic oxygenated (pH = 2.7-3.2) surface water. This difference in mineralogy is attributed to the redox and acidity conditions. In the surface water, activities of SO4 2- and H + control the proportions of minerals in the assemblage and More Cu, Zn, and Ni were precipitated from the ground water than from surface waters due to the higher initial content of Fe and higher pH of ground water. The concentrations of the metals were not significantly changed in the surface water because of limited sorption of cations at low pH. The affinity of the metals to the precipitate rather than the solution is in the order Cu>Zn>Ni. Sequential extraction indicated that Ni and Zn accumulate in poorly crystalline schwertmannite, while Cu concentrates in crystalline phases (goethite and jarosite). However, schwertmannite, as the principal phase in most of the precipitates, contains a significant proportion of Cu. During the recrystallization of metastable schwertmannite to goethite, the metals could be redistributed and released back into the mine water.
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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 | 0.000 | 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 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".