Current scientific understanding of the environmental biosafety of transgenic fish and shellfish
Bibliographic record
Abstract
A fluorescent zebrafish was the first genetically engineered animal to be \nmarketed, and biotechnologists are developing many transgenic fish and \nshellfish. Biosafety science is not sufficiently advanced to be able to draw \nscientifically reliable and broadly trusted conclusions about the environmental \neffects of these animals. The science is best developed for identifying hazards \nposed by environmental spread of a transgenic fish or shellfish and least \ndeveloped for assessing potential ecological harms of spread. Environmental \nspread of certain transgenic fish or shellfish could be an indirect route of entry \ninto the human food supply. The management of predicted environmental risks is \nin its infancy and has thus far focused on the first step of the risk management \nprocess, i.e. risk reduction, via a few confinement methods. There is a critical \nneed to improve scientific methods of environmental safety assessment and \nmanagement and to gather empirical data needed to substantiate biosafety \nconclusions and to effectively manage transgenic fish and shellfish. Scientists \nand potentially affected parties should participate in prioritising the knowledge \ngaps to be addressed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".