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Record W4411047435 · doi:10.1016/j.cep.2025.110377

Process development for biooxidation of refractory gold ore using Ferroplasma acidophilum: A bench-scale case study of gold recovery

2025· article· en· W4411047435 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Engineering and Processing - Process Intensification · 2025
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversity of OttawaYork University
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaMitacsYork University
KeywordsRefractory (planetary science)Gold oreMetallurgyMaterials science

Abstract

fetched live from OpenAlex

This study investigates the effects of biooxidation using Ferroplasma acidiphilum on gold recovery from high-grade (HGOS) and low-grade ore samples (LGOS). Pretreatment methods are caaried out in stirred tank reactors and column tests. Results showed that the stirred tank reactor yielded higher recovery rates for key elements, with gold recovery reaching 55 % for HGOS compared to 40 % for LGOS using the column test. Optimal conditions for biooxidation were identified, including aeration flow rates of 1.0–1.5 L/min and agitation speeds of 300–450 rpm, which facilitated effective microbial activity and pyrite dissolution. During cyanidation, gold recovery was highest at a pH of 10.5, with up to 60 % recovery at 8 (g/L) NaCN. However, at pH levels above 11, gold recovery decreased to around 40 % due to competing chemical species and metal hydroxide precipitation. The study also found that extending cyanidation time enhanced gold recovery, with significant increases observed within the first 10 h.

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.

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 score0.313
Threshold uncertainty score0.914

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)0.0000.000

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 head0.028
GPT teacher head0.281
Teacher spread0.253 · 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