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Record W4386823766 · doi:10.15407/steelcast2023.02.083

Trends of the foundry market of Ukraine in the first quarter of the XXI century

2023· article· en· W4386823766 on OpenAlexaboutno aff
V.A. Gnatush, V.S. Doroshenko, S.I. Klymenko

Bibliographic record

VenueMetal and Casting of Ukraine · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsFoundryUkrainianBusinessProduction (economics)Quarter (Canadian coin)Modernization theoryEconomyEngineeringEconomic growthEconomicsGeographyMechanical engineering

Abstract

fetched live from OpenAlex

An analysis of the state of foundry production in Ukraine is presented. The foundry industry of Ukraine in the 21st century significantly reduced its production indicators, which is due to the influence of such factors as the stagnation of industries that consume metal castings, as well as a decrease in exports. This situation has been negatively affected by the COVID-19 pandemic, as well as the global foundry industry, due to a decrease in demand for castings from end manufacturers. It was predicted that positive developments should be expected in the near future. However, russia's attack on Ukraine on February 24, 2022 made a significant correction in the development of the global economy, and, accordingly, in the functioning of the world foundry industry. Ukrainian companies in the foundry industry felt the impact of the war, some of them suffered partial destruction of their production premises. Large foundry enterprises of Ukraine are mostly located in the south-eastern regions, which were the most affected by hostilities. At the same time, in order to reflect the real situation in the foundry industry of Ukraine, it is advisable to organize the collection of real data regarding the production of castings from various alloys in the country, as well as regarding the export and import of foundry products. This will make it possible to make effective decisions regarding the program of modernization of the industry and the development of industries that consume domestic metal castings. Ultimately, this will help increase the competitiveness of Ukrainian products and increase revenues to the budget of Ukraine. To assess the direction of development of foundry production in advanced countries of the world, the statistical data of the leading countries regarding the production of castings and in more detail such countries as Poland, Germany and the USA are given. The structure of cast products produced in the world is in constant dynamics and there is a constant change in the ratio of the volumes of castings produced from various alloys. Recent years have been characterized by a tendency to reduce the production of castings from steel and gray iron with a simultaneous increase in the share of castings from highstrength cast iron and aluminum alloys.

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)0.002
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 score0.302
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.213
Teacher spread0.187 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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