Epidemiological profile of Clonorchis sinensis infection in one community, Guangdong, People’s Republic of China
Bibliographic record
Abstract
BACKGROUND: Clonorchiasis caused by ingesting improperly prepared fish ranks among the most important but still neglected food-borne parasitic diseases, especially in the People's Republic of China (P.R. China). To promote the implementation of interventions efficiently, the demonstration of an epidemiological profile of Clonorchis sinensis infection is essential in hyper-epidemic areas. METHODS: In one community with higher levels of economic development in Guangdong province, P.R. China, villagers were motivated to provide stool samples for examining helminth eggs. Then, those infected with C. sinensis completed the structured questionnaire including demographical characteristics, knowledge and behavior. RESULTS: A total of 293 villagers infected with C. sinensis participated in questionnaire investigation. Among them, 94.54% were adult and 93.17% were indigenous. The geometric mean of C. sinensis eggs per gram of feces in the children, adult females and adult males was 58, 291 and 443, respectively. The divergence between knowledge and behavior in the adults, especially the adult males, was shown. Out of 228 persons eating raw fish, 160 did it more frequently at restaurants, the proportion of which varied in different populations, showing 25.00%, 54.88% and 80.28% in the children, adult females and adult males, respectively. CONCLUSIONS: Different interventions need to be adopted in different populations. Chemotherapy should be prioritized in the adults, especially the adult males. In addition, health education targeting the children, is essential and may play a crucial role in controlling clonorchiasis in the long term. In order to successfully control clonorchiasis, intervention in the restaurant should not be overlooked in some endemic areas.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".