Analysis of the European Union's Lawsuit Against Indonesia Regarding the Ban on Nickel Ore Exports
Bibliographic record
Abstract
Nickel is a metal that has the characteristics of a silvery-white color with the characteristics of strength, heat resistance, light weight and corrosion resistance with the chemical formula Ni. It has good electrical and thermal conductivity making it suitable for coating copper, iron and aluminum to prevent corrosion. Nickel was first discovered and developed by Cronstedt in 1751, in a mineral called Nicolite (Kupfernickel), which was found in the Sudbury region, Ontario, Canada, a nickel-producing area of 30% of the world's demand for nickel metal. One of the countries with the largest nickel reserves is Indonesia. According to several experts, it is estimated that Indonesia has nickel reserves of more than 1 billion tons of nickel. The largest distribution of nickel reserves is in the eastern part of Indonesia. The distribution of nickel in Indonesia and the distribution of nickel mining in Indonesia today, among others, are found on the islands of Sulawesi (Southeast and South Sulawesi), Maluku and Papua. Unfortunately, currently a lot of Indonesian nickel is exported in the form of raw material, so the selling price is very cheap. Thus, government support is very much needed to improve nickel processing, such as support for ease of licensing, clear and transparent rules and regulations. This support can be seen in the issuance of a decree by the Ministry of Energy and Mineral Resources Number: 549.Pers/04 SJI/2019 dated 2 September 2019 concerning "Nickel Ore Cannot be Exported Again as of January 2020".
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".