ANALYSIS OF MONITORING RESULTS OF NINE CATEGORIES OF FOODS IN XUANHAN COUNTY FROM 2004 TO 2007
Bibliographic record
Abstract
[Objective]To understand health status of local food production in Xuanhan County,master the key of food supervision and monitoring in future.[Methods]Retrospectivly analyzed food hygiene situation of cooked meat and products,cakes,and other nine categories of foods in Xuanhan County from 2004 to 2007,and the qualification situation of various types of food for nearly four years,and the disqualification situation of various types of food items.[Results]The qualified rates of nine categories of foods were basically the same in each year;sampling qualified rates of cooked meat and products and cakes were decreasing. The lowest qualified rate was in the third quarter.[Conclusion]Food hygiene situation of local production is worrying,in particular it should increase the intensity of supervision and monitoring of cooked meat and products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".