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Record W6960528403 · doi:10.13590/j.cjfh.2023.10.017

Comparison on regulations of temperature requirements of critical control links in food cold chain process between China and foreign countries

2023· article· en· W6960528403 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Supply Chain Traceability
Canadian institutionsnot available
Fundersnot available
KeywordsCold chainChinaStandardizationProcess (computing)CommissionQuality (philosophy)Food safetyControl (management)

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.217
GPT teacher head0.516
Teacher spread0.299 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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