Evolution and optimization of China’s natural gas import spatial framework
Bibliographic record
Abstract
With the increasing dependence on gas import,and for the purpose of the natural gas supply security in China,it is extremely essential to establish a rational and safe natural gas import spatial framework.In this paper,China’s natural gas import spatial framework was quantitatively analyzed for its evolution and optimization and dynamically compared with that of Japan and Korea by using such indexes as market share,diversity index,import market structure optimization index,matching degree between import market structure and exporter comparative advantage and import governance safety index.It is shown that China’s import market structure is being continuously optimized and the effects of diversification strategy emerged,but China still falls behind Japan and Korea in many aspects.Optimization pathways and directions were proposed from the perspectives of comparative advantage and governance safety.It is necessary to develop LNG import markets in Norway and Brunei,to strengthen LNG import shares in Australia and Qatar,and to explore the possibility to import LNG from Canada and America.As for pipeline natural gas,it is necessary to construct natural gas strategic import pathways continuously in NW,NE and SW China and to strengthen the energy diplomacy with Russia and Burma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".