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Record W4404545577 · doi:10.3390/min14111177

Preliminary Beneficiation Studies of Quartz Samples from the Northwest Territories, Canada

2024· article· en· W4404545577 on OpenAlexafffundabout
Hanyu Zhang, Gideon Lambiv Dzemua, Qi Liu

Bibliographic record

VenueMinerals · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsGovernment of Northwest TerritoriesUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQuartzBeneficiationImpurityGeologyLeaching (pedology)MineralogyMaterials scienceGeochemistryMetallurgyChemistry

Abstract

fetched live from OpenAlex

Three quartz-rich geologic materials—vein quartz from the Great Bear Magmatic Zone, massive quartz from the Nechalacho rare earth deposit, and quartz sands from the Chedabucto silica sand deposit along the shores of the Northern Arm of the Great Slave Lake, Northwest Territories of Canada—were evaluated for their amenability to physical beneficiation into high-purity quartz (HPQ). The samples were subjected to various treatment processes, including crushing, grinding, calcining and quenching, acid leaching, wet high-intensity magnetic separation (WHIMS), and reverse flotation. After treatment, both the core and sand quartz samples met the requirements for HPQ, making them suitable for use in the production of semiconductor filters, liquid crystal displays (LCDs), and optical glass. However, the Al-bearing impurity content in the vein quartz products remained relatively high, and most of these impurities were dispersed in the quartz lattice, requiring further processing to meet the purity standards for HPQ required by these industries.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.474

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 head0.022
GPT teacher head0.240
Teacher spread0.219 · 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 designNot applicable
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

Citations2
Published2024
Admission routes3
Has abstractyes

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