Bibliographic record
Abstract
Objective To study the epidemic regularity and characteristics of food poisoning in Zhejiang schools from 2004 to 2012,and to provide basis for preventive measures of food safety in school. Methods Analysis was conducted on the incidence data of food poisoning reported in schools through the public health emergency surveillance system in Zhejiang from 2004 to 2012. Results A total of 66 food poisoning events in schools were reported in Zhejiang from 2004 to 2012. A total of 1 514 students and teachers were involved,no people were dead. Most food poisoning events occurred in 2nd,3rd and 4th quarter. The proportions of food poisoning occurred in primary schools and secondary schools,colleges,infant institutes,and other schools were 65. 15%, 16. 67%,12. 12% and 6. 06%. About 75. 76% of food poisoning happened in canteens,10. 61% in mobile vendors and snack shops near the schools. Bacteria( 54. 5%),and plant( 15. 15%) were main factors resulted in food poisoning. Conclusion Supervision should be implemented according to different epidemiological characteristics in canteens,mobile vendors,snack shops near the schools,and commissary in the schools. Propaganda and education should be strengthened to dining room staffs,teachers and students.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".