Speciation and quantification of surface gold in carbonaceous matter by TOF‐SIMS: a new approach in characterizing losses during the gold recovery process
Bibliographic record
Abstract
Abstract An increasing number of low‐grade gold ore deposits are characterized by the presence of gold as solid solution into the mineral matrix of sulphide minerals which is not directly amenable to gold cyanidation. In order to liberate this submicroscopic gold the ore has to be oxidized before being subjected to gold cyanidation and exctraction. This is mainly done by autoclave pressure oxidation (AC POX) or roasting, two major technologies used by the mining industry. Very often, these ores contain an active carbonaceous compound which has the ability to adsorb, or preg‐rob gold from the cyanide solution. Gold recovery can be adversely affected by preg‐robbing on inherent carbonaceous material during autoclave pressure oxidation of sulphide ores. The time of flight (TOF) SIMS (TOF‐SIMS) technique has been applied for direct determination of gold species on individual carbonaceous particulates from AC POX stream samples. The speciation of the gold preg‐robbed on carbonaceous matter from CIL tail sample showed presence of both metallic gold and Au(CN) 2 compound. Direct quantification of the metallic and compound gold provided an estimate for the fraction of gold losses due to preg‐robbing in carbonaceous matter. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".