Import dependency and import security of rapeseed and rapeseed oil in China
Bibliographic record
Abstract
In order to identify the source reliability and lower the risks of China’s importing rapeseed and rapeseed oil,the relationship between China and the source countries of China’s rapeseed and rapeseed oil import market was studied.Based on analysis of China’s rapeseed and rapeseed oil import market structure,the study focused on the following aspects:identifying the proportion of the value share of China’s rapeseed and rapeseed oil imported from each source country to the total import value from all the world(I1),the proportion of the value share of rapeseed and rapeseed oil exported from each source country to China to the total export value to the world(I2),and the total trade balance(Index B)between China and each country was also taken into account.The dependency coefficients(I3、I5)of China’s import and import safety were estimated in this paper.Research results indicated that China’s import of rapeseed and rapeseed oil mainly depended on Canada,but the dependency coefficient went down gradually by showing that the rapeseed indexes I3and I5dropped from 12.781 8and 4.322 4in 2005to 2.662 5and 1.032 7in2012respectively,and the rapeseed oil indexes I3and I5dropped from 5.079 8and 0.906 2to 2.232 7and 0.856 1respectively.Research results indicated that Canada is the safe source of China’s rapeseed and rapeseed oil import and it is economic rationality to import more rapeseed rather than rapeseed oil.Some countermeasures and advice have been given by the authors in the end.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".