Laws and Regulations for Protection and Patent of Soybean Genetic Resources
Bibliographic record
Abstract
China is the recognized soybean mother country and owns the most plenty of soybean genetic resources in the World. China had already been the major country of soybean producer and exporter. and ranks behind is USA and Brazil in soybean products and become net importing country due to the development of soybean sciences and technologies in America counties from the recent half-century. Now soybean become the most compelling trade crop in international crop product trade in China. With the rapidly developments of agricultural biotechnology and more aware of protection of intellectual property, there are much more unprecedented challenges in the fields of research, development and utilizations of Chinese soybean production, especially in joining the WTO. Soybean as well-known resources of plant protein, edible oil and forage plant in China should been urgently protected in the levels of genetic resources and new varieties based on the laws and regulations. In this paper authors mainly introduced the laws and regulations related to protection of genetic resources and new varieties of soybean and analyzed the feasible of patent in soybean genetic resources.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".