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Record W1712095985

IDENTIFYING THE PRIORITY APPROACH OF SALES ACTIVITIES FOR IRON-ORE ENTERPRISES

2013· article· en· W1712095985 on OpenAlex
Olha Tymoshenko

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

VenueInstitutional Repository National Mining University of Ukraine (National Mining University of Ukraine) · 2013
Typearticle
Languageen
FieldEngineering
TopicEngineering and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIron oreBusinessSales managementOperations managementMarketingCommerceIndustrial organizationEconomicsMetallurgy
DOInot available

Abstract

fetched live from OpenAlex

The market of iron-ore raw materials characterized as a market oligopoly competition dominated by three multinational Corporation (Vale, Rio Tinto and BHP Billiton).Their share in world trade is about 61%, that allows to dictate pricing in the market.The company LKAB (Sweden), SNIM (Mauritania), CVG (Venezuela), Kumba (South Africa), Quebec Cartier (Canada) Metaloinvest (Russia), Metinvest (Ukraine) and Ferrexpo (OJSC "Poltava ore "(PGOK), Ukraine) has also a significant share in world trade.In recent years these companies have increased exports and diversified geographical structure.Poltava Mining (PGOK) -is export-oriented enterprise that sells almost all products in the foreign market (East and Central Europe, Asia), that competes with Northern Mining, Russian mills of Metalloinvest and Karelia pellets and suppliers from Sweden, Brazil, Australia, South Africa, India and Canada.The main advantages of PGOK in comparison with competitors it should be attributed favorable geographical location of the plant and infrastructure for shipments of pellets, large reserves of ore and high-tech facilities for its processing; favorable strategic partnerships with key customers, the industry average level of production costs and delivery of pellets.The export of Poltava GOK in 2011 increased by 5.4% to 9.506 million tons, of which 49% -is flotation pellets with Fe content 65%.It should be noted that the production of flotation pellets this year increased by 4.8% to 4.256 million tons, however the production of pellets with Fe content 62% -fell by 3.3% to 4.807 million tons This indicates a high consumer demand for more high-quality raw materials that is prepared and PGOK focusing to meet the needs of their clients.However, the decline of global economic conditions and market of steel and iron ore pellets made the majority of European consumers to reduce their production capacity and, accordingly, purchasing of raw materials.Therefore, the volume of pellets deliveries of PGOK market in Eastern and Central Europe in 2011 fell by 20% in comparison with 2010 to 5.263 million tons, and its share has fallen from 73% to 55% of the total exports of the plant (Table 1).It should be noted that last year Poltava GOK in general worked at full capacity, despite the adverse market conditions and the external pressure from the internal economic constraints (the growth of annual production inflation since 2011 on 15.6%, the tariff for electricity and gas etc.).However, PGOK compensated growth of average cost of output by increasing the production volume and efficiency,

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.894

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 studies0.0010.001
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 head0.015
GPT teacher head0.187
Teacher spread0.172 · 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