ARD/AMD potential of the waste management area : Goldcorp Inc., Red Lake Mine Division, Balmertown, Ontario : final report.
Bibliographic record
Abstract
As part of the decommissioning plans of Goldcorp Inc., the potential of acid generation \nfrom the tailings was addressed with acid base accounting tests, The occurrence of acid \ngenerating minerals along with neutralizing minerals is extremely varied and the limited \nnumber of ABA tests lead to uncertain results. Boojum Research Ltd. was retained to \nassess the acid generation potential further. From a field investigation of the surface water on the tailings it was concluded, that within \none year of cessation of tailings discharge, the physical/chemical conditions ofthe ponded \nwater resembles those ofthe surrounding fresh water and supports considerable biological \nactivity. The pH in ponded water on the tailings ranged from 7.0 to 8.6 and in the \nsediments/tailings pH values as high as 9.1 were measured. The electrical conductivity \nwas low, with values ranging between 200 umhos/cm to 1000 umhoslcm. These surface \nwaters would facilitate ecological approaches to decommissioning. To determine a reliable estimate of the quantity of acid generating minerals in the tailings, \ndata were extracted from mineralogical and milling records in addition to chemical analysis \nreported for tailings. The data consistently produce an average of 1.5% S, 6.7% Fe and \n2.7% Al. Sequential extraction of the tailings for mineral association produced a weight loss \nof 42%, the remaining 68% of the tailings are totally inert. Of the digestible fraction, 29% \nconsisted of alkalinity generating minerals and 21% of potentially acid generating minerals, \nthus the neutralizing potential mass is equal to that of the acid generating mass. Through the extraction of weathering products which had formed in the tailings the \nongoing oxidation, leading to acid generation and the concurrent neutralization was \ndetermined. Tailings material collected from old (32 years) and new ( 10 years) tailings \nponds was leached with distilled water. The leach solutions were all above pH 7 and \nalkalinity between 50 to 210 mg.L-’ CaCO, equivalent. The tailings material clearly has \nremaining neutralization potential left. In the leachate from visually oxidizing tailings, 36% of S in the solids was mobilized with water, along with 14% Ca afler 10 years of exposure \nin the tailings pond. In the visually unoxidized sample exposed for the same time only \n2.3% of the S and 2.2% of the Ca could be liberated by distilled water. Acid generation and \nits concurrent neutralization appears to be localized in pockets of the tailings pond. The \nrate of acid generation and neutralization has not been determined. It can be concluded \nthat effluent problems normally associated with acid generating tailings will not be \nencountered for the Goldcorp Inc. tailings area. The concentrate stored on the tailings is \nacid generating. It is at present unclear, if some piezometer water quality is affected by this material.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 0.009 |
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".