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Record W4390915210 · doi:10.9719/eeg.2023.56.6.781

Situation of Utilization and Geological Occurrences of Critical Minerals(Graphite, REE, Ni, Li, and V) Used for a High-tech Industry

2023· article· en· W4390915210 on OpenAlex
Sang‐Mo Koh, Bum Han Lee, Chul‐Ho Heo, Otgon‐Erdene Davaasuren

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEconomic and Environmental Geology · 2023
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
FundersMinistry of Science and ICT, South KoreaKorea Institute of Geoscience and Mineral Resources
KeywordsGraphiteGeochemistryGeologyMetallurgyMineralogyMining engineeringEarth scienceEnvironmental scienceMaterials science

Abstract

fetched live from OpenAlex

Recently, there has been a rapid response from mineral-demanding countries for securing critical minerals in a high tech industries.Graphite, while overwhelmingly dominated by China in production, is changing in global supply due to the exponential growth in EV battery sector, with active exploration in East Africa.Rare earth elements are essential raw materials widely used in advanced industries.Globally, there are ongoing developments in the production of REEs from three main deposit types: carbonatite, laterite, and ion-adsorption clay types.While China's production has decreased somewhat, it still maintains overwhelming dominance in this sector.Recent changes over the past few years include the rapid emergence of Myanmar and increased production in Vietnam.Nickel has been used in various chemical and metal industries for a long time, but recently, its significance in the market has been increasing, particularly in the battery sector.Worldwide, nickel deposits can be broadly classified into two types: laterite-type, which are derived from ultramafic rocks, and ultramafic hosted sulfide-type.It is predicted that the development of sulfide-type, primarily in Australia, will continue to grow, while the development of laterite-type is expected to be promoted in Indonesia.This is largely driven by the growing demand for nickel in response to the demand for lithium-ion batteries.The global lithium ores are produced in three main types: brine lake (78%), rock/mineral (19%), and clay types (3%).Rock/mineral type has a slightly higher grade compared to brine lake type, but they are less abundant.Chile, Argentina, and the United States primarily produce lithium from brine lake deposits, while Australia and China extract lithium from both brine lake and rock/mineral sources.Canada, on the other hand, exclusively produces lithium from rock/mineral type.Vanadium has traditionally been used in steel alloys, accounting for approximately 90% of its usage.However, there is a growing trend in the use for vanadium redox flow batteries, particularly for large-scale energy storage applications.The global sources of vanadium can be broadly categorized into two main types: vanadium contained in iron ore (81%) produced from mines and vanadium recovered from by-products (secondary sources, 18%).The primary source, accounting for 81%, is vanadiumiron ores, with 70% derived from vanadium slag in the steel making process and 30% from ore mined in primary sources.Intermediate vanadium oxides are manufactured from these sources.Vanadium deposits are classified into four types: vanadiferous titanomagnetite (VTM), sandstone-hosted, shale-hosted, and vanadate types.Currently, only the VTM-type ore is being produced.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.243

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 head0.029
GPT teacher head0.263
Teacher spread0.234 · 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