Modification of the existing maximum residue levels and setting of import tolerances for oxathiapiprolin in various commodities
Bibliographic record
Abstract
In accordance with Article 6 of Regulation (EC) No 396/2005, the applicant Du Pont de Nemours GmbH submitted two requests to the competent national authority in Ireland to modify the existing EU maximum residue levels (MRLs) and to set import tolerances for oxathiapiprolin in various plant commodities in order to accommodate the intended EU uses and the authorised uses of this active substance in China, Canada and the United States. The data submitted in support of the request were found to be sufficient to derive MRL proposals for all crops under consideration, except for Brussels sprouts and peas (without pods), for which residue data were either not submitted or were insufficient to support the use. Adequate analytical methods for enforcement are available to control the residues of oxathiapiprolin in commodities under consideration at the validated limit of quantification (LOQ) of 0.01 mg/kg. Based on the risk assessment results, EFSA concluded that, taking into account the existing and the intended uses, the long-term intake of residues of oxathiapiprolin is unlikely to present a risk to consumer 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 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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".