STRATEGIC ROLE OF OIL PIPELINES IN EU ENERGY SUPPLY
Bibliographic record
Abstract
The oil pipelines have a strategic importance in the energy supply of the European Union (EU), especially given the fact that in the next two decades the crude oil will continue to be a dominant energy source, accounting for approx. 30% of the primary energy consumption, along with a reduction in the petroleum product consumption and growth in renewables. Europe has a widespread network of oil pipelines of approx. 22,5 thousand kilometres (without Russia), connecting refineries to import oil ports or to land-based crude oil sources. The refineries of the Central Eastern Europe are supplied mainly from the Druzhba oil pipeline. Recently, these refineries have diversified their crude oil supply routes and sources, by sea imports from the North Sea, the Middle East, Canada and others (Poland) or by the TAL – IKL oil pipelines (Czech Republic) and the JANAF oil pipeline (Hungary, Slovakia and the Czech Republic). Given the insufficient diversification of crude oil supply precisely of the Central Eastern European region, particularly the landlocked countries (and refineries respectively), the EU has envisaged, among the projects of common interests, also six connection oil pipelines with terminals. At the same time, they are the only pipelines planned to be constructed in Europe and financed by the oil companies’ funds. The oil pipeline and storage companies, as well as other oil companies, have a social responsibility as regards the energy supply, yet also a responsibility as regards their successful performance and development, thus investing considerable funds into modernisations, upgrades, protection, safety and security, etc. The oil pipeline companies hastily modify their strategies by expanding business and becoming more and more transport-storage-energy oriented, and by investing in the flow reversal of oil pipelines and connection pipelines, storage capacities, as well as in enhancement of efficiency and flexibility of oil pipeline and storage infrastructures.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".