Factors of competitiveness of LNG export projects
Bibliographic record
Abstract
As a result of the development of liquefaction, storage, transportation and regasification technologies, the attractiveness of LNG projects is steadily growing — in some cases, such projects are becoming more competitive than traditional pipeline solutions. The range of solutions for natural gas liquefaction projects is very wide, but low-tonnage LNG provides greater mobility and high speed of project implementation, cause of the usage of the simple low-efficiency technologies. Medium-capacity natural gas liquefaction plants can be built in environment where there are not enough resources to create a large-capacity project, and enable the usage of relatively small and remote fields, including off shore areas. For Russia, an important advantage of medium-tonnage technologies is that they can be developed in a relatively short time. The positive experience of government support for LNG exports in Canada is noteworthy. The government of this state strives to create conditions for environmentally responsible energy production and use, while ensuring the growth of the Canadian economy, as well as the availability of reliable and competitive energy sources and the protection of energy infrastructure. As for the portfolio of orders for Russian projects for natural gas liquefaction, for example, at present, in the Yamal-LNG project, Russian orders account for only 30 %, and the goal is at least 70 %. To achieve this goal, government support is required: concessional lending and tax incentives. For LNG production in the Arctic zone of the Russian Federation, with the support of the state Corporation Rosatom, a bench-testing base for import-substituting equipment is being created in the Nizhny Novgorod region. Government support for LNG projects should also include improving the regulatory framework. Russia is taking an important step towards developing its hydrocarbon reserves in the Arctic. Special attention should be paid to the measures of state support that are provided to exporters in the context of the pandemic, including in the field of LNG sales, in particular, ensuring sustainable lending to the real sector of the economy with the provision of state guarantees and subsidies.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".