Human infections and co-infections with helminths in a rural population in Guichi, Anhui Province, China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Helminth infections are believed to be common in tropical and subtropical countries. A cross-sectional study was carried out in two villages located in Guichi District in Anhui Province, the People’s Republic of China, where multiparasitism was investigated using parasitological tests. The data collected were fitted to Bayesian multi-level models to profile risk factors for helminth infections. The prevalence of <em>Schistosoma</em> (<em>S.</em>) <em>japonicum</em>, <em>Ascaris</em> (<em>A.</em>) <em>lumbricoides</em> and <em>Trichuris</em> (<em>T.</em>) <em>trichiura</em> were 0.43% (range: 0-0.87% at the village level), 2.28% (range: 1.69-2.88%), and 0.21% (range: 0-0.42%), respectively. No hookworm infection was found. With regard to multiparasitism, only a 33-year-old female was found to be co-infected with <em>S. japonicum</em> and <em>A. lumbricoides</em>. Multiparasitism was unexpectedly rare in the study area, which contrasts with results from other studies carried out elsewhere in the country. The long-term usage of albendazole for individuals serologically positive for schistosomiasis may be the main reason, but this needs to be confirmed by future studies.
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.
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 | 0.000 |
| 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 it