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Record W4413460581 · doi:10.1093/jme/tjaf105

Mosquitoes in small urban spaces: identification of blood meals and flight distances of engorged females in the southern Great Plains of the United States

2025· article· en· W4413460581 on OpenAlexfundno aff
Brandon E. Henriquez, Scott R. Loss, Bruce H. Noden

Bibliographic record

VenueJournal of Medical Entomology · 2025
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureHatchU.S. Department of AgricultureCenters for Disease Control and PreventionOklahoma State Department of HealthOklahoma Agricultural Experiment StationOklahoma State University
KeywordsBiologyIdentification (biology)Ecology

Abstract

fetched live from OpenAlex

Vector-borne disease transmission can only occur when host(s), vector(s), and pathogen(s) interact in a given environment. While many studies have focused on these interactions in large urban areas, there is a need for habitat-focused studies in small urban areas where human populations are often close to wildlife and livestock. The aim of the current study was to identify the bloodmeal sources of mosquitoes in a small urban area in the southern Great Plains of the United States. Using 2 trap types, bloodmeals from 12 different hosts were detected, and the most frequently detected bloodmeal hosts were white-tailed deer, cow, and horse. The known locations of livestock at each site made it possible to identify the nearest location where mosquitoes could have fed on cows, horses, and alpacas, and we demonstrated that mosquitoes could fly distances between 200 m and 1.2 km from the bloodmeal host to the resting trap location within 30 h after taking blood. This study highlights the opportunities that are available within small urban areas to discover important host-vector relationships.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.184

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.290
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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