Mosquito fauna inhabiting water bodies in the urban environment of Córdoba city, Argentina, following a St. Louis encephalitis outbreak
Bibliographic record
Abstract
An understanding of urban aquatic environments as mosquito larval habitats is necessary to prioritize sites for surveillance and control of arbovirus vectors in urban areas. Natural and artificial water bodies at ground level that may be larval mosquito habitats in Córdoba city, Argentina were surveyed. Data on the characteristics of aquatic sites and the presence and abundance of mosquito larvae and pupae were collected in the summer of 2006, coinciding with the first report of human WNV and following an outbreak of St. Louis encephalitis in 2005. Eight species in the genera Aedes, Culex, and Mansonia were identified. At 64.2% (34 of 53) of the sites, only one species was collected, while 3.8% (2 of 53) had three associated species, the highest richness found per site. Culex quinquefasciatus represented over 99% (out of 32,729) of the specimens. It was also the most widely distributed and detected under diverse habitat conditions. Although puddles and semi-permanent pools harbored a greater number of species, drainages and channels may be more relevant as risk factors from an epidemiological point of view because they showed the highest larval densities, mainly of Cx. quinquefasciatus (vector of SLE and WNV). Also, higher densities of this species were associated with stormwater runoff and sewage water, thus water management systems should be targeted and closely monitored for mosquito control purposes.
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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".