THE CURRENT STATE TRENDS OF PRODUCTION AND USE OF PETROLEUM BITUMEN ABROAD AND IN THE KAZAKHSTAN
Bibliographic record
Abstract
The world production of petroleum bitumen for road construction is considered, where residual petroleum road bitumen is mainly used, from which more than 80% of roads are built in the West. The absolute leaders of the bitumen market are the USA, Canada and China. In terms of development of oil bitumen production potential, Russia ranks second among the developed countries of the world after the United States, but at the same time lags behind the US level by 3 times, but is ahead of Canada, which ranks third and has 7.0% of global production capacity. The leading positions in the Russian bitumen market are occupied by companies Gazprom Neft, Rosneft, and Lukoil. They account for almost 80% of the total bitumen production in the Russian Federation. The needs of the domestic bitumen market in the Republic of Kazakhstan are met by four large producers of road bitumen, with a total capacity of 1.2 million tons per year. Data on the development of the bitumen industry of the Republic of Kazakhstan for 5 years are analyzed and the dynamics of the volume of the bitumen market in Kazakhstan is shown. The volume of bitumen production in the Republic of Kazakhstan has doubled since 2015.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".