Sustainable Research on World Potassium Resource Trade Based on Complex Network Theory
Bibliographic record
Abstract
As a national strategic resource, trade activities of potassium resources（K） have changed its state of ownership. Futures and spot trading forms in the international market are mainly primary processed ore and deep-processed products. So, K trade can be replaced by the potassium salt trade. Its international trade will affect a country’s strategic resource management, and increase national resource security risks. Thence, it is necessary to study the evolution of international trade in K. This paper has constructed a weighted and directed complex network model of K trade using UN Comtrade 2000-2016 data and analyzed the scale and activity of international trade of K, trade relations, trade flow distribution and the importance of countries. By analyzing the international trade data of K in 224 countries, it is found that trade is active year by year and K is becoming more significant. From network density and diameter, resource allocation is more convenient. The network cluster is growing. It shows that some countries form trade groups. The correlation coefficient of degrees is less than 0, indicating that the trade relationship between small and major trade countries is enhancing. And, the reciprocal coefficient is between 0.1 and 0.35, showing that the trade order is poor. Moreover, it presents a state that the greater the country’s degree, the smaller the difference in trade flow distribution. So, resource flows in countries with more trade relations can promote a balanced distribution of K. Finally, from countries’ trade influence and hub status, Canada is a leading trade country, and the US, the Russian Federation, China and Brazil are trade-led countries. They are the main source of K flows. China, the Netherlands, the US, France and India are important hubs. So, countries should strengthen bilateral trade relations. So as to ensure the SD of international trade in K, major trading countries should focus on the exploit of K and improve the level of production and processing tech. Countries should also enhance their hub role to facilitate the flow of K. China, as a large country in agriculture and K demand, should increase self-sufficiency to reduce import dependence risks. Besides, attention should be paid to market changes in major trading countries and to reducing risks by adding the number of trade countries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".