Bibliographic record
Abstract
Objective To analyze the data of food- borne diseases active surveillance system during 2011. 7-2012. 6 in Futian district of Shenzhen city,thus to provide references for development of strategies and measures. Methods The case definition of the surveillance system was formulated and data collected in food-borne diseases active surveillance system during 2011. 7 to 2012. 6 was analyzed with respect of population distribution,time distribution,diagnostic categories,suspected food and region distribution. Results Totally 2,224 food-borne disease cases were reported,males accounted for 49. 3 % and female,55. 88 %. The majority was within the age of 18-34 years,accounting for 49. 4 %. The peak of reported cases appeared in the fourth quarter of 2011,especially in October. Most cases were diagnosed as bacterial food- borne disease( 63. 9 %) and the majority of suspect food was meat and meat products( 36. 0%). Conclusion Food- borne disease active surveillance system can reflect the trend of food-borne diseases in the district and is also an important access to acquire the relevant information.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".