<i>Trypanosoma cruzi</i> Infection in an Indigenous Kariña Community in Eastern Venezuela
Bibliographic record
Abstract
We investigated the seroprevalence of Trypanosoma cruzi infection in an indigenous Kariña population in eastern Venezuela. A total of 175 serum samples were collected in the community of Piñantal during February 2009. Interviews targeting socioeconomic and environmental factors associated with the T. cruzi transmission were also conducted. Samples were evaluated using trypomastigote excreted/secreted antigens (TESAs) in an ELISA format. TESA-ELISA positive samples were confirmed by indirect haemagglutination (HAI) (Wiener). A nonsystematic collection of vectors was also undertaken. T. cruzi seroprevalence was 7.43% according to both assays, and the mean age of infected patients was 48.61±10.40 years (range 34 to 73 years). The vector infection rate was 20.00% (2/10). T. cruzi seropositivity was associated with a history of triatomine bites, the ability to recognize the vector and poor knowledge about Chagas disease, but no associations were found with gender, house type, knowledge of how the disease is transmitted, or the presence of vectors or animals inside dwellings. To our knowledge, this is the first study of the seroprevalence of T. cruzi in an indigenous population in eastern Venezuela. All of the epidemiological variables required for the establishment of active vectorial transmission of T. cruzi were present in this community.
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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 | 0.001 |
| 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 | 0.001 | 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".