TOWARD SOURCE CONTROL OF ACID ROCK DRAINAGE
Bibliographic record
Abstract
Source control of acid rock drainage (ARD) requires consideration of both biological and abiotic mechanisms of metal sulfide oxidation. A promising approach is to couple a biocide with phosphate for application to sulfidic waste materials. This approach aims to 1) inhibit or kill with thiocyanate (SCN) the iron-oxidizing acidophilic microorganisms that accelerate sulfide oxidation and 2) precipitate FePO 4 and AlPO 4 , thereby removing ferric ion oxidant and Lewis acidity, and, in the process, armoring the surface of pyrite to retard its abiotic oxidation. Thiocyanate effectively reduces sulfide biooxidation if it is applied efficiently and is not washed out of the system by rainfall or adsorbed to the rock. Several sources of phosphate including phosphate rock, waste material and agricultural products were characterized and tested in combination with SCN for their ability to retard oxidation of sulfidic waste rock. Waste rock sources include samples from base metal and precious metal mines and a coal mine. The acid neutralizing capacities (ANC) of different sources of phosphate were compared and evaluated using an artificial ARD solution which included iron and aluminum sulfates. Thiocyanate alone in laboratory tests sharply reduced ARD production, approaching the abiotic rate of sulfide oxidation. Whether thiocyanate plus phosphate further reduced ARD production depended on the mineral sulfide composition of the waste rock and the parameter measured. The abiotic sulfide oxidation rate of sphalerite-containing waste rock was reduced with phosphate treatment, most likely by removal of residual ferric iron from leach solutions. Phosphate did not further reduce abiotic sulfide oxidation rates with a pyritic waste rock, but did significantly reduce the soluble iron and other metal content of leachates.
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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) | 0.000 | 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".