Technical Note on the quality of DNA sequencing for the molecular characterisation of genetically modified plants
Bibliographic record
Abstract
As part of the risk assessment (RA) requirements for genetically modified (GM) plants, according to Regulation (EU) No 503/2013 and the EFSA guidance on the RA of food and feed from GM plants (EFSA GMO Panel, 2011), applicants need to perform a molecular characterisation of the DNA sequences inserted in the GM plant genome. The European Commission has mandated EFSA to develop a technical note to the applicants on, and checking of, the quality of the methodology, analysis and reporting covering complete sequencing of the insert and flanking regions, insertion site analysis of the GM event, and generational stability and integrity. This Technical Note puts together requirements and recommendations for when DNA sequencing is part of the molecular characterisation of GM plants, in particular for the characterisation of the inserted genetic material at each insertion site and flanking regions, the determination of the copy number of all detectable inserts, and the analysis of the genetic stability of the inserts, when addressed by Sanger sequencing or NGS. This document reflects the current knowledge in scientific-technical methods for generating and verifying, in a standardised manner, DNA sequencing data in the context of RA of GM plants. From 1 October 2018, this Technical Note will replace the JRC guideline of 2016 (updated April 2017) related to the verification and quality assessment of the sequencing of the insert(s) and flanking regions. It does not take into consideration the verification and validation of the detection method which remains under the remit of the JRC.
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 | 0.048 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.023 | 0.048 |
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".