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Record W1991381420 · doi:10.1080/08827500490441341

INNOVATIVE HYDROMETALLURGICAL PROCESSES FOR THE PRIMARY PROCESSING OF ZINC

2004· article· en· W1991381420 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.

Bibliographic record

VenueMineral Processing and Extractive Metallurgy Review · 2004
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsQuébec Science (Canada)
Fundersnot available
KeywordsZincPrimary (astronomy)MetallurgyProcess engineeringComputer scienceMaterials scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The zinc industry has been in the forefront of hydrometallurgical developments for almost a century. The development of pressure leaching in the 1980s and the development of atmospheric direct leaching in the 1990s for treating zinc-sulphide concentrates have resulted in a number of zinc-refinery expansions without an increase in roasting capacity. Likewise, solvent extraction techniques are now used for the hydrometallurgical treatment of zinc-oxide ores on an industrial scale. The treatment of poor and complex zinc-sulphide resources has been extensively studied using processes as diverse as pyrolusite leaching and heap bioleaching. Finally, the precipitation of relatively pure zinc oxide at the mine site, a process that has been proven to be technically feasible very recently, may significantly change the paradigm of primary zinc production. The author would like to thank the Editor-in-Chief, Dr. S. Komar Kawatra, for his invitation to publish in Mineral Processing and Extractive Metallurgy Review and for his kind patience during the manuscript preparation. He would like also to thank an anonymous reviewer for some very helpful comments and the meticulous editing of the text.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.286
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