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PERSPECTIVES OF THE WORLD STEEL AND COKE MARKETS (on the materials of the international conference "EuroCoke Summit", Amsterdam, 2021)

2021· article· en· W4205862102 on OpenAlexaboutno aff
E.T. Kovalev

Bibliographic record

VenueJournal of Coal Chemistry · 2021
Typearticle
Languageen
FieldEnergy
TopicCoal and Coke Industries Research
Canadian institutionsnot available
Fundersnot available
KeywordsChinaSummitCokeCoalLimitingEngineeringWork (physics)BusinessPolitical scienceNatural resource economicsWaste managementEconomicsGeography

Abstract

fetched live from OpenAlex

The article is devoted to the review of the main materials of the international conference Eurocoke-2021, which took place on October 5-6 in Amsterdam, the Netherlands. Despite the fact that the conference is named as European, the representatives of the world's leading firms and research centers from the EU, England, Australia, India, USA, China, Ukraine and other countries took part in its work. The article summarizes the main results and conclusions of the reports and discussions. As the most of speakers noted, that despite the impact of the global recession and the logistical difficulties caused by the COVID-19 pandemic, as well as the China's ban to use Australian coal, a significant change in the global coal market is not expected in the near future. China's trade policy has led mainly to a redistribution of markets for Australian, American, Canadian and Russian coal. Technologies and researches to replace some of the components of the coking coal charge with a cheaper coal grades or carbonaceous materials of plant origin in order to reduce the cost of coke and steel are still relevant. The strict requirements for limiting greenhouse gas emissions are forcing coke and steel producers to modernize the existing traditional production facilities (including using integrated technologies) to reduce emissions and improve the efficiency of the CO2 capturing and utilization. In the world steel production in the next decade, a significant increase in the share of technologies focused on abandoning coke and blast furnace production is hardly possible due to the high cost and duration of the corresponding projects. Keywords: coke production, steel industry, world coking coal market, steel market, trends, recession, logistics, COVID-19, greenhouse gas emissions, decarbonization, direct iron reduction, integrated technologies, stamped charge coking, biomass, catalysis. Corresponding author E.T. Kovalev, e-mail: post@ukhin.org.ua

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 categoriesInsufficient payload (model declined to judge)
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 score0.038
Threshold uncertainty score0.997

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.268
Teacher spread0.242 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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