Comparison on regulations of temperature requirements of critical control links in food cold chain process between China and foreign countries
Bibliographic record
Abstract
ObjectiveTo provide suggestions for the improvement of the standards of China， the management situation of international organizations and other countries on temperature requirements of food cold chain process was studied.MethodsThe standards between China and Codex Alimentarius Commission （CAC）， International Organization for Standardization （ISO）， the European Union， the United States， Canada and Australia/New Zealand were compared and analyzed. And the issues of most concerning were raised. The suggestion of cold chain logistics temperature control of China was put forward.ResultsThe standards of other countries were basically recommended operating requirements. There were fewer requirements for specific temperatures. However， the standards system in our country was a combination of compulsory and recommended and there were more requirements for specific temperatures. In both domestic and foreign standards， temperature fluctuation was allowed， and the importance of vehicle precooling， monitoring， transportation tools， and so on were emphasized. However， foreign standards were more emphasized on process management. In the future， China should strengthen the establishment of recommendatory operation rules.ConclusionThe standard management on temperature requirement of the food cold chain in China conforms to international standards. The food safety standards are relatively reasonable. China should take good measures to the quality standards， and promote healthy and harmonious development of this industry.
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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 | 0.007 | 0.007 |
| 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 | 0.000 |
| 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".