The regulation of transgenic trees in North America.
Bibliographic record
Abstract
Canada and the United States have both developed strong, science-based systems for the regulation of transgenic plants to ensure environmental protection. In both countries transgenic plants cannot be introduced into commerce unless they have been critically evaluated for environmental safety. The frame-work for the regulation of transgenic plants in Canada and the U.S. is comparable, however there are significant differences. In Canada, the Canadian Food Inspection Agency is responsible for the regulation of importation and environmental release of plants with novel traits that includes, but is not limited to, transgenic plants. In the U.S., the Animal and Plant Health Inspection Service is responsible for the regulation of importation, interstate movement, and environmental release of transgenic plants. The U.S. Environmental Protection Agency registers certain pesticides produced in transgenic plants prior to their distribution and sale and establishes tolerances for the pesticides in the plants. Details of the Canadian and U.S. regulatory systems are presented, including information on the key criteria utilized in environmental safety assessments, with an emphasis on some unique challenges posed by transgenic trees. To date, the U.S. has authorized the release of one transgenie tree species (papaya) and has allowed approximately 124 confined trials of transgenic trees. Canada has authorized only two transgenie tree trials thus far.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".