Fish and fishery products quality grading standards of China,CAC,the United States of America,European Union,Canada,Japanand their Comparison
Bibliographic record
Abstract
Fish and fishery products quality grading is to rate and classify fish and fishery products according to their quality.The products intended for direct consumption or further processing may have different properties,such as integrity,odour/flavour,texture,even foreign matters and processing defectives.Quality grading of commodities are important for consumer's purchase,marketing and international trade.As quality grading standards are significant for the nation's international competitiveness,markets and quality grade standards in China and in some developed countries should be well studied to learn their strongpoints.In this paper,standards in some international organizations and some developed countries and regions were introduced and compared,such as those in CAC,the United States of America,European Union,Canada and Japan.The results showed that there exists a great difference of the factors rated and product species between China and other counterparts,which could serve as good experience for designing better and more comprehensive quality and safety grading standards.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".