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Record W3035943817 · doi:10.2903/j.efsa.2020.6133

Setting of import tolerances, modification of existing maximum residue levels and evaluation of confirmatory data following the Article 12 MRL review for flupyradifurone and DFA

2020· article· en· W3035943817 on OpenAlexaboutno aff
Maria Anastassiadou, Giovanni Bernasconi, Alba Brancato, Luis Carrasco Cabrera, Luna Greco, Samira Jarrah, Aija Kazocina, Renata Leuschner, José Oriol Magrans, Ileana Miron, Stéfanie Nave, Ragnor Pedersen, Hermine Reich, Alejandro Rojas, Angela Sacchi, Miguel Santos, Alois Stanek, Anne Theobald, Bénédicte Vagenende, Alessia Verani

Bibliographic record

VenueEFSA Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural safety and regulations
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean commissionAgricultural scienceEuropean unionResidue (chemistry)BiotechnologyToxicologyMathematicsBusinessBiology

Abstract

fetched live from OpenAlex

In accordance with Article 6 of Regulation (EC) No 396/2005, the applicants Bayer CropScience AG and Bayer SAS submitted two requests to the competent national authority in the Netherlands to set import tolerances and to modify existing EU maximum residue levels (MRLs) for the active substance flupyradifurone and its metabolite difluoroacetic acid (DFA) in various crops. The application also included the request to evaluate the confirmatory data related to residues that were identified in the framework of the peer review of flupyradifurone under Regulation (EC) No 1107/2009 as not available. The data submitted in support of intended and authorised uses were found to be sufficient to derive MRL proposals for flupyradifurone and DFA in all crops under consideration except for prickly pear and hops; for grapefruit, pome fruits, grape leaves and witloof, further risk management discussion is recommended to decide on the appropriate MRL. Furthermore, EFSA recommended risk management discussion to examine different options to deal with DFA residues in crops that can be grown in crop rotation. The calculated livestock dietary burdens indicated that existing EU MRLs for flupyradifurone and DFA in animal commodities need to be modified. Adequate analytical methods for enforcement are available to control the residues of flupyradifurone and the DFA in plant and animal matrices. The submitted data are considered sufficient to address the data gaps related to residues which were identified in the framework of the EU pesticides peer review, and thus, the footnotes set for DFA and flupyradifurone MRLs in the Commission Regulation (EU) 2016/1902 can be deleted. Based on the consumer exposure assessment, acute consumer exposure concerns could not be excluded for tomatoes, melons, celery and processed escaroles. Hence, the raising of the existing MRLs for flupyradifurone in these crops is not recommended. For these four crops, MRL proposals for DFA were derived, which reflect the uptake of residues via soil resulting from previous use of flupyradifurone. For the remaining commodities of plant and animal origin, EFSA concludes that the intended EU uses and authorised US and Canadian uses of flupyradifurone and resulting residues of DFA will not result in chronic or acute consumer exposure exceeding the toxicological reference values and therefore is unlikely to pose a risk to consumers' health.

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)0.060
metaresearch head score (Gemma)0.063
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.063
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.002
Science and technology studies0.0040.003
Scholarly communication0.0050.003
Open science0.0040.003
Research integrity0.0100.005
Insufficient payload (model declined to judge)0.0080.006

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 head0.268
GPT teacher head0.349
Teacher spread0.080 · 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
GenreEmpirical

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

Citations8
Published2020
Admission routes1
Has abstractyes

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