Analysis on the Hygienic Quality Situation of Tableware in Catering Industry,Zoucheng City,2010
Bibliographic record
Abstract
[Objective]To analyze the hygienic quality situation of tableware sterilization effect in catering industry in Zoucheng city and ensure the safety of consumers,to provide evidences for the sanitation management to develop health management measures for tableware and cooker.[Methods]Investigation was made on the hygienic quality situation of tableware sterilization effect in 106 catering industries in Zoucheng city in 2010,analysis was made on the results and comparison was made with the previous data,then to provide the countermeasures.[Results]The total qualification rate was 83.26%.There were differences among the four quarters.The differences of qualification rates were significant(P0.01) between the first quarter(91.46%) and the third quarter(76.15%);The qualification rate of different types was 96.80%(hotel restaurant)、89.05%(diner),76.82%(restaurant),65.40%(food stalls),and that between units with different types was significant(P0.01).Among all the tableware samples,the qualification rate of plate(65.02%) was the lowest,the cup(96.35%) was the highest and the differences of qualification rates were significant(P0.01).The qualification rate of tableware which sterilized by steam and water boiling methods was higher(95.68%) than other methods(P0.01).[Conclusion]The qualification rate of tableware in Zoucheng is lower and it is not in the line with the national standards.It is important to strengthen monitoring and detection in catering units.The important measures to raise the qualification rate of tableware is to manage the street stalls centralized and regionally,the other important measure is to sterilize the tableware centralized.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".