Effect of Tableware Disinfection in Catering Units of Shimen County from 2006 to 2008
Bibliographic record
Abstract
Objective To investigate the status of tableware disinfection in catering units of Shimen County,and to provide a scientific basis for prevention of food-borne diseases and food poisoning.Method Data on disinfection effect of various tableware in catering units in Shimen County from 2006 to 2008 were analyzed.Results Totally 28,516 tableware samples collected from catering units in Shimen from 2006 to 2008 were tested,24,376 of them were up to standard,with the total eligible rate of 85%.82%,85%,89% of them were up to standard in 2006,2007 and 2008 respectively;the difference was statistically significant(P0.01).The qualified rate was the highest in the first quarter(90%)and the lowest in the third quarter(81%).There was a difference in the qualified rate among the different quarters(P0.01).The qualified rate of chopsticks and cups was the highest(89%),while that of the plates was the lowest(80%).There was a difference of the qualified rate in different tableware(P0.01).Conclusions Tableware disinfection in catering units of Shimen County is effective,but supervision and inspection must be continuously strengthened.The regulations of disinfection and sanitary management must be implemented in an all-round way.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".