SYNTHETIC BIOLOGY AND GENETIC MANIPULATION: Risks, promises and responsibilities
Bibliographic record
Abstract
Abstract As a result of the biotechnological advance, synthetic biology has been applied from the improvement of food to the creation of new organisms. This article investigates, from a bioethical perspective, the benefits, risks and threats to life, arising from the production, manipulation and, especially, the creation of synthesized DNAs that do not exist in nature. Bioethics reports from the White House and the Bioethics Committee of Portugal and Spain contributed to the discussion. The progress of technoscience, without the proper ethical capacity for evaluation, can produce results that compromise the social development, environmental preservation, human dignity, and biosphere life in the future. In this sense, the achievements of synthetic biology have been shown to be ambivalent, because hopes are mixed with threats, with unpredictable results to the diversity of life of the biosphere, which makes prudence the virtue par excellence.
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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 | 0.026 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.039 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".