Bibliographic record
Abstract
modified agricultural products, or have been in commercial pn> duction for about a decade. In that time, the number of acres devoted to biotech crops such as corn, cotton, and soybeans has increased dramatically with a billion cumulative acres worldwide. Although controversy often accompanies a discussion of biotech crops, it is safe to say they are here to stay. Biotech crops are generally subject to environmental and other regulations in their country of origin. See, e.g. , Blake A. Biles, Agricultural Biotechnology: The U.S. Perspective, 18 Nat. RESOURCES & Env't 12 (Summer 2003). An emerging issue facing biotech crops is whether they will be subject to environmental regulation by the receiving country through the regulation of their bulk transportation. This article focuses on how emerging international environmental laws will govern biotech crops, requiring regulatory approval before biotech crops can continue to be transported in bulk commodities shipments to major overseas markets of the United States and Canada. Emerging laws regulating biotech crops in nations importing agricultural commodities from the United States will drive changes in state and federal laws in the United States as exporters react to overseas developments. Two recent decisions in particular could transform the laws regulating transportation of genetically engineered biotech crops. In the first decision the World Trade Organization (WTO) ruled in favor of the United States, Canada, and Argentina invalidating the moratorium the European Union (EU) imposed from 1998 to 2003 on approving biotech crops imported by EU nations for food or animal feed. The second decision arrived in March 2006 when the 134 parties to the Cartagena Protocol on Biosafety to the Convention on Biological Diversity (Biosafety Protocol or BSP) finally reached consensus, after a decade of contentious negotiations, concerning the identification of particular biotech crops in commodities shipments. These two decisions intertwine in their legal effect and point toward a future where the first wave of biotech crops could gain a firm foothold in feeding the world, while a few reluctant nations slowly come to recognize the benefits that biotech crops can bring. While overseas nations grow more accepting of biotech crops, however, major
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".