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Record W2586249289 · doi:10.1080/21645698.2017.1289305

New GMO regulations for old: Determining a new future for EU crop biotechnology

2017· review· en· W2586249289 on OpenAlexaboutno aff
John Davison, Klaus Ammann

Bibliographic record

VenueGM crops & food · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsBiotechnologyProcess (computing)Agricultural biotechnologyBusinessAgricultureRisk analysis (engineering)BiologyComputer science

Abstract

fetched live from OpenAlex

In this review, current EU GMO regulations are subjected to a point-by point analysis to determine their suitability for agriculture in modern Europe. Our analysis concerns present GMO regulations as well as suggestions for possible new regulations for genome editing and New Breeding Techniques (for which no regulations presently exist). Firstly, the present GMO regulations stem from the early days of recombinant DNA and are not adapted to current scientific understanding on this subject. Scientific understanding of GMOs has changed and these regulations are now, not only unfit for their original purpose, but, the purpose itself is now no longer scientifically valid. Indeed, they defy scientific, economic, and even common, sense. A major EU regulatory preconception is that GM crops are basically different from their parent crops. Thus, the EU regulations are “process based” regulations that discriminate against GMOs simply because they are GMOs. However current scientific evidence shows a blending of classical crops and their GMO counterparts with no clear demarcation line between them. Canada has a “product based” approach and determines the safety of each new crop variety independently of the process used to obtain it. We advise that the EC re-writes it outdated regulations and moves toward such a product based approach. Secondly, over the last few years new genomic editing techniques (sometimes called New Breeding Techniques) have evolved. These techniques are basically mutagenesis techniques that can generate genomic diversity and have vast potential for crop improvement. They are not GMO based techniques (any more than mutagenesis is a GMO technique), since in many cases no new DNA is introduced. Thus they cannot simply be lumped together with GMOs (as many anti-GMO NGOs would prefer). The EU currently has no regulations to cover these new techniques. In this review, we make suggestions as to how these new gene edited crops may be regulated. The EU is at a turning point where the wrong decision could destroy European agricultural competitively for decades to come.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0040.008
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.047
GPT teacher head0.388
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations116
Published2017
Admission routes1
Has abstractyes

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