Bibliographic record
Abstract
With the continued development of the natural market,China's natural consumption grows rapidly,whereas the natural reserve mechanism is relatively incomplete,which has led to the phenomenon of frequent gas famine in recent years.Therefore,we introduce the natural reserves status from many aspects of basic information,natural storage means and scale,gas storage system,regulation and laws in different countries respectively including the USA,Canada,Britain,France,Spain,Italy,Germany,Japan,and South Korea.On the basis of this,we summarize their experiences as follows:①Gas storage has been one of the necessary means for safe and stable supply in those consumption countries;②Various storage systems such as underground storage,LNG storage,gas field reserves,etc.have to be prepared according to each country's resources and consumption situation;③Those countries with huge yearly consumption or those relying on large imports have to possess a large capacity of storage,thus having longer storage days of reserves;④The management system of storage is quite different in different countries,only the USA operates its storage,transportation,and supply in a highly commercial way;⑤Although Japan is the only one among these countries which issues the Law of Natural Gas Storage,the other countries have enacted various degrees of laws on the construction and management of natural storage.Hopefully,these experiences will provide a valuable reference for China to establish its strategic natural reserves as early as possible.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".