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Record W2049229818 · doi:10.1515/htmp-2012-0099

Thermodynamic Analysis of the Sulphation Roasting of Enargite Concentrates

2012· article· en· W2049229818 on OpenAlexaff
Brian Chambers, C.A. Pickles, J.G. PEACEY

Bibliographic record

VenueHigh Temperature Materials and Processes · 2012
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsQueen's University
Fundersnot available
KeywordsRoastingElectrowinningPyrometallurgyLeaching (pedology)CopperMetallurgyHydrometallurgyChalcopyriteArsenicMaterials scienceSulfationGold cyanidationChemistryEnvironmental scienceCyanideElectrode

Abstract

fetched live from OpenAlex

Abstract The mining industry is under increasing pressure to assess the extraction of value from complex copper ores, such as those containing enargite (Cu 3 AsS 4 ), due to the rising demand for copper and gold. A sulphation roast, weak acid leach, and electrowinning process flowsheet has been studied to address the treatment of copper concentrates containing significant amounts of enargite. Copper is recovered from the calcine by acid leaching, with most of the arsenic being fixed in the leach residue after gold extraction by cyanidation. The relative simplicity of roasting combined with proven hydrometallurgical technologies has the potential to be economically advantageous and readily scaled for commercial operation. Based on a proposed reaction mechanism, a thermodynamic analysis has been performed using HSC Chemistry® 6.1 in order to establish an operating window and assess the overall potential feasibility of the proposed flowsheet.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2012
Admission routes1
Has abstractyes

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