CIL Gold Loss Characterization within Oxidized Leach Tails: Creating a Synergistic Approach between Mineralogical Characterization, Diagnostic Leach Tests, and Preg-Robbing Tests
Bibliographic record
Abstract
A double refractory gold ore contains gold particles locked in sulphides, solid-solution in arsenopyrite, and preg-robbing material such as carbonaceous matter, and so on. The diagnostic leach test (DLT) and preg-robbing (PR) approaches are widely used to investigate the occurrence and the distribution of refractory gold. DLT serves to qualitatively evaluate the gold occurrences within the ore. Preg-robbing, or the ore’s capacity to fix dissolved gold, is evaluated to determine physical surface interactions (preg-borrowing) and chemical interactions (preg-robbing). The objective of this project is to characterize the refractory gold in Agnico Eagle Mine’s Kittilä ore using the DLT and PRT approaches coupled with mineralogical analyses to confirm testing. The studied material was sampled from the metallurgical circuit following carbon in leach (CIL) treatment at the outlet of the autoclave in order to investigate the effect of the autoclave treatment on the occurrence and distribution of gold. Different reagents were used in the DLT procedure: sodium carbonate (Na2CO3), sodium hydroxide (NaOH), hydrochloric acid (HCl), and nitric acid (HNO3). The final residue was roasted at a temperature of around 900 °C. These reagents were selected based on the mineralogical composition of the studied samples. After each leaching test/roasting, cyanide leaching with activated carbon was required to recover gold cyanide. The results show that gold is present in two forms (native and/or refractory): to a small extent in its native form and in its refractory form as association with sulfide minerals (i.e., arsenopyrite and pyrite) and autoclave secondary minerals that have been produced during the oxidation and neutralization processes such as iron oxides, iron sulfates, and calcium sulfate (i.e., hematite and jarosite), along with carbonaceous matter. The results of DLT indicate that 25–35% of the gold in the tails is nonrecoverable, as it is locked in silicates, and 20–40% is autoclave products. A regrind can help to mitigate the gold losses by liberating the Au-bearing sulphide minerals encapsulated within silicates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".