Prevalence and Determinants of Cryptosporidium Infection in an Underdeveloped Rural Region of Southwestern China
Bibliographic record
Abstract
Few studies have focused on the epidemiology of Cryptosporidium in resource-challenged settings in China. We report a community-based cross-sectional study to investigate the prevalence of Cryptosporidium infection and its risk factors and associations with hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus (HIV) infections. The prevalence of Cryptosporidium infection was 12.6% (95% confidence interval = 11.0–14.3). Individuals living in households with ≥ 5 family members and raising domestic pigs tended to have a greater risk of Cryptosporidium infection. In addition, Cryptosporidium infection was significantly associated with HBV infection. There were no significant associations of Cryptosporidium infection with HIV viral load and HBV viral load. Further studies are needed to determine the association of Cryptosporidium infection with HBV infection.
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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 | 0.001 | 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) | 0.001 | 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".