Shell‐isolated nanoparticle‐enhanced Raman spectroscopy characterization of oxide ores during thiosulfate‐mediated gold leaching
Bibliographic record
Abstract
An applied approach for in situ characterization of oxide ore samples exposed to a thiosulfate‐based leaching solution with shell‐isolated nanoparticle‐enhanced Raman spectroscopy (SHINERS) is discussed. Differences in passive layer growth during thiosulfate leaching were observed in the SHINERS spectra between the untreated and pressure oxidation (POX)‐treated oxide ore samples received from Barrick Gold Corporation. The SHINERS spectra revealed that the passive layer at the untreated oxide ore–electrolyte interface contains metal sulfides and significant quantities of polysulfide chains of variable lengths after longer exposure to the leaching solution. However, the passive layer observed with the POX‐treated sample was found to be predominantly metal sulfides with only a small quantity of polysulfide chains. From these results, it was concluded that the POX pretreatment process may successfully destroy or inactivate minerals found in the ore that are responsible for catalysing thiosulfate decomposition into polysulfides which results in low gold extraction efficiencies. Copyright © 2016 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 | 0.000 |
| 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) | 0.001 | 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 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".