MINING AND METALLURGICAL COMPLEX OF UKRAINE: CURRENT TRENDS AND RESULTS
Bibliographic record
Abstract
The article analyzes the production and sales results of the enterprises of the mining and metallurgical complex of Ukraine (hereinafter MMC) in 2020, in the first quarter and for four months of 2021, as well as the preconditions that developed in 2019. It was determined that the results of production of MMC of Ukraine in 2019 were the worst for the entire period of the existence of independent Ukraine. The article analyzes the factors of ineffective work of metallurgical and mining enterprises in this period. In 2020, the situation was aggravated by the COVID-19 pandemic. Steel production declined, while pig iron and rolled products increased marginally compared to 2019. Exports of iron ore increased by almost a quarter, which means that the success of the ore segment partially offset the difficulties in the metallurgical sector. Success factors for the ore segment of the mining and metallurgical complex of Ukraine in 2020 were: rapid recovery of China after quarantine, effective measures to support the economy by China and European countries, high demand and prices for ore, rapid recovery of business activity and low level of stocks, which led to an increase in prices for metal products. It was determined that in the first quarter of 2021 the production of pig iron, rolled products, sinter increased compared to the same indicator in 2020, but the production of coke, steel and pipes decreased. The export of the main products of the mining and metallurgical complex has grown significantly. In April 2021, there was a drop in exports of iron ore and ferrous metals compared to March, but in general, for four months of 2021, the dynamics of exports is positive. The article examines positive trends (growth in prices for iron ore raw materials, demand and prices for steel and rolled products), as well as risks and threats that have arisen in the market and which will affect the efficiency of mining and metallurgical enterprises in 2021 and in the long term (a slowdown in the growth of the Ukrainian economy and countries-consumers of mining and metallurgical products, a high level of protectionism, insufficient protection of the domestic market from imports of metal products, the need for significant investments in improving the environmental friendliness of metallurgical production and increasing environmental costs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".