Investigation on Sterilization of Tableware in Caterings in Huaiyin District of Huaian Municipality from 2004 to 2005
Bibliographic record
Abstract
[Objective]To understand the sterilization of tableware in caterings in Huaiyin district of Huaian municipality,provide scientific basis for improving disinfection of tableware.[Methods]The qualified rate was 62.4% in 2004,while it was 75.3% in 2005.There was a difference(P0.01).The qualified rate in large hotels was 74.0%,it was 71.9% in middle-sized hotels and 65.4% in small-sized hotels.There was a difference of the qualified rate in different hotels(P0.01).83.1% of the glasses,which were not be used often,were up to standard,while 65.0% of the bowls which wereused more often were up to standard.There was a difference of the qualified rate in different kind of tableware(P0.01).The qualified rate was 73.2% in the fourth quarter and 64.7%,66.9% in the second and third quarter.The qualified rate in 2005(75.3%) was higher than that in 2004(62.4%).[Conclusion]The sterilization of tableware in middle and small-sized hotels was bad,supervision must be strengthened.
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 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 | 0.001 | 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".