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Record W2143684068 · doi:10.1603/me13007

Host-Seeking Mosquito Distribution in Habitat Mosaics of Southern Great Plains Cross-Timbers

2013· article· en· W2143684068 on OpenAlexfundno aff
Valerie O’Brien, Michael H. Reiskind

Bibliographic record

VenueJournal of Medical Entomology · 2013
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersOklahoma Agricultural Experiment StationCommission for Environmental CooperationOklahoma Center for the Advancement of Science and TechnologyOklahoma State University
KeywordsEntomologyHabitatLibrary scienceState (computer science)ArchaeologyBiologyEcologyGeographyMathematicsComputer science

Abstract

fetched live from OpenAlex

Landscape fragmentation often increases contact between humans, wildlife, and potential disease vectors. We examined how adult host-seeking mosquitoes respond to small-scale habitat differences within southern Great Plains cross-timber habitat mosaics in northern Oklahoma consisting of eastern red cedar (Juniperus virginianus L.) woodlands, mixed-deciduous woodlands, and adjacent grasslands. Mosquitoes responded most markedly to an overall grassland-woodland habitat gradient, with species separating by habitat based largely on tree density. Differences in abundance of host-seeking females occurred at fine spatial scales, sometimes varying dramatically over distances as little as 200 m when tree density changed abruptly. Tree type was not as important as tree density, although the West Nile virus vector Culex tarsalis Coquillett showed a greater affinity for areas containing eastern red cedar than for deciduous woodlands. The invasive Aedes albopictus Skuse showed equal affinity for both tree types. Conversion of grassland habitats in the Great Plains to more vegetated environments associated with humans (towns and homesteads) and the invasion of grasslands by eastern red cedar may change the species composition of mosquito, bird, and mammal assemblages and potentially alter arbovirus exposure for humans.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.300
Teacher spread0.290 · 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.

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

Citations24
Published2013
Admission routes1
Has abstractyes

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