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Record W3199794523 · doi:10.3390/min11091021

Flotation of Carbonaceous Matter from a Double Refractory Gold Ore: The Effect of MIBC on Flotation Performance and Kinetics

2021· article· en· W3199794523 on OpenAlexafffund
Sugyeong Lee, Charlotte E. Gibson, Ahmad Ghahreman

Bibliographic record

VenueMinerals · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centres of ExcellenceBarrick Gold Corporation
KeywordsChemistryKineticsBubbleOrganic matterLeaching (pedology)Froth flotationGold oreMetallurgyMaterials scienceEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

The use of alkaline pressure oxidation to pretreat refractory gold ore often results in insufficient gold recovery (<60%) in downstream thiosulfate leaching. To improve gold recovery, flotation was considered for the separation of carbonaceous matter (C-matter). In this study, the effect of MIBC on C-matter flotation was investigated to understand the role of the frother in bubble and froth formation and on flotation kinetics. MIBC dosages between 30 and 150 g/t were used in combination with 500 g/t of kerosene as a collector. The results showed that the recovery and selectivity of C-matter were improved with increasing MIBC dosages. Improved selectivity at higher MIBC dosages was attributed to faster C-matter recovery as bubble size decreased to the critical coalescence concentration (CCC) and to changes to the foam structure. Analysis of flotation kinetics showed that the flotation rate increased as the MIBC dosage increased due to the decreasing bubble size and the reduced induction time caused by the interaction between the collector and the frother. The results of this study explain the role of MIBC in C-matter flotation and can be used as a design basis for scavenger-cleaner flotation testing. Overall, the results show the potential for flotation as a means to improve gold recovery in thiosulfate leaching through the removal of C-matter.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.235
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2021
Admission routes2
Has abstractyes

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