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Record W2953553146 · doi:10.29227/im-2018-01-05

Market for Critical Raw Materials and its Influence on Mineral Prices

2018· article· en· W2953553146 on OpenAlex
Jaroslav Dvořáček, Radmila Sousedíková, Zuzana KUDELOVÁ

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

VenueInżynieria Mineralna · 2018
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsRaw materialMineralNatural resource economicsEnvironmental scienceBusinessEconomicsMaterials scienceMetallurgyEcologyBiology

Abstract

fetched live from OpenAlex

The paper has focused on market for critical raw materials and its influence on mineral prices. Usually ores and ore products are deemed critical raw materials if they mostly or totally come from foreign countries, have difficult replacement, and are vital for the Nation’s economy, especially for defence issues. Tungsten, niobium, graphite and lithium were chosen for analysis from the critical mineral commodities declared by the European Commission and the Government of the Czech Republic. An analysis of these mineral commodity market conditions has been made, and their impacts on particular mineral availability and price have been assessed. As regards tungsten supplies, there are relatively many producer countries with the existing or developing extraction structures, but China has at its disposal 60% of the deposits. Lithium reserves are sufficient, but supplies are highly concentrated – four producer companies deliver about 90% of lithium in the world. Also niobium supplies are extremely concentrated, in the period, 2009–2012, two Brazilian mines and a single Canadian one produced 99% of niobium in the world. The biggest world producer of natural graphite is China that dominates 70% of the market. Natural resources of the above mentioned mineral commodities are not critical. The Earth’s crust deposits are sufficient for long - -term exploitation, and what’s more, a technology has been patented for lithium recycling. What rather matters is the issue of the free play of market forces. The theoretical preconditions for the free play of market forces and balanced price convergence – market presence of many various producers and many customers – are disturbed by producer structure, high concentration of mining com - panies and countries. Free market interference is implied in dominance of individual producer countries or production companies, and their ability to decide about production levels and related prices. Nevertheless, the inevitable rise of mineral commodity prices will mean that exploitation of some sources, which are currently deemed uneconomical, may become interesting.

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 score0.260
Threshold uncertainty score0.674

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)0.0010.000

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 head0.017
GPT teacher head0.296
Teacher spread0.279 · 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