Comparison of Legislation of Veterinary Drug Residue Limits in the Animal-source Products at Home and Abroad
Bibliographic record
Abstract
Recent years,with rapid development of the national economy and i-mprovement of the qulity of people's life,people pay more attention to the pr-oblem of food safty.Control of veterinary drug residue is one of the most im-portant part of task in resolving food satfty problem.There are series laws,re-gulations and restriction standards against the problem of veterinary drug residue have been formulated in wordwide.This article reviews relevant laws and reg-ulations which restrict on veterinary drugs management and maximum residue 1-imits index among Codex Alimentarius Commission,European Union,Canada and China. Compared from the managed number of veterinary drugs,residual food category and typical veterinary drugs maximum limits index.Finally,this article shows that the regulation and residue limits for veterinary drugs have th-eir own distinguishing feature among China and other organization,region and country.In particular,the difference on maximum limits index is obvious,which is one of the main reason about the technical barriers of animal-source pr-oducts trade between China and foreign countries.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".