Bioleaching of Ultramafic Tailings by Acidithiobacillus spp. for CO2 Sequestration
Bibliographic record
Abstract
Bioleaching experiments using various acid-generating substances, i.e., metal sulfides and elemental sulfur, were conducted to demonstrate the accelerated dissolution of chrysotile tailings collected from an asbestos mine near Clinton Creek, Yukon, Canada. Columns, possessing an acid-generating substance colonized with Acidithiobacillus sp., produced leachates with magnesium concentrations that were an order of magnitude greater than mine site waters or control column leachates. In addition, chrysotile tailings were efficient at neutralizing acidity, which resulted in the immobilization of metals (Fe, Cu, Zn) associated with the metal sulfide mine tailings that were used to generate acid. This suggests that tailings from acid mine drainage environments may be utilized to enhance chrysotile dissolution without polluting “downstream” ecosystems. These results demonstrate that the addition of an acid-generating substance in conjunction with a microbial catalyst can significantly enhance the release of magnesium ions, which are then available for the precipitation of carbonate minerals. This process, as part of a carbon dioxide sequestration program, has implications for reducing net greenhouse gas emissions in the mining industry.
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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 | 0.001 |
| 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".