Assessing the persistence of DNA in decomposing leaves of genetically modified poplar trees
Bibliographic record
Abstract
DNA transformation of forest tree species is now a striking reality and offers the possibility to generate transgenic trees with useful new characteristics. However, it is important to make the proper environmental assessment of these transgenic trees when established in field trials. For instance, the DNA released into the soil by decaying leaves and roots from the transgenic trees may become available for incorporation by soil microbes. The objective of this study was to investigate the persistence of recombinant plant marker genes in decomposing transgenic poplar leaf material. We studied the stability of the DNA encoding the neomycin phosphotransferase II resistance marker used in tree genetic engineering. DNA persistence in the environment was determined by placing transgenic poplar leaves in permeable bags that were located on weeds, on the soil, and below the soil and left under natural conditions on the site of a field trial for up to 12 months. This work is the first quantitative analysis of tree DNA stability in a natural forest environment. Our data indicate that fragments of the genetically modified DNA are not detectable in the field for more than 4 months.
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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 | 0.000 | 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 | 0.000 |
| 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 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".