Respuesta doméstica a las recomendaciones sanitarias de intervención sobre ambiente y perros en una localidad con transmisión de leishmaniasis visceral (Pto. Iguazú, Argentina, 2014–2016)
Bibliographic record
Abstract
Introduction: Visceral leishmaniasis (VL) is an emerging parasitic disease in Argentina. In Puerto Iguazú, border with Brazil and Paraguay, vector and canine cases were registered in 2010; and in 2014 and 2015 there were two human cases. Objective: The objective of this article is to analyze changes at the micro-scale level after informing the cohabitants of the diagnosis of canine LV (LVC), letting them know the environmental management strategies to reduce contact with the vector. Method: It is a descriptive researh, which investigated in two moments (2014 and 2016) a non-probabilistic sample distributed based on the criterion of the best scenario for the presence of the vector (n = 55). Sampling points with the presence of vectors and at least one dog with LVC (n = 6/55) were selected, after a first entomological and veterinary diagnosis raking. Results: A single household implemented the suggested modifications. The changes were not enough to control the transmission. The hypothesis is that the control measures require intervention at a meso-scale (the neighborhood instead of the home), taking into account the real radius of vector dispersion. Conclusions: The risk of human infection due to VL is related to the way of life, including interspecies relationships. The human-dog relationships combine speciesism and post-humanism, which limits the effectiveness of "responsible ownership" as model of a healthy bond.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".