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Record W2946159226 · doi:10.1111/jvec.12336

Modeled distributions of<i>Aedes japonicus japonicus</i>and<i>Aedes togoi</i>(Diptera: Culicidae) in the United States, Canada, and northern Latin America

2019· article· en· W2946159226 on OpenAlexaffabout
Daniel A.H. Peach, Max Almond, Joshua Cornelis Pol

Bibliographic record

VenueJournal of Vector Ecology · 2019
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBiologyLatin AmericansHabitatEcologyAedesLarvaLaw

Abstract

fetched live from OpenAlex

The Asian bush mosquito, Aedes japonicus japonicus, and the coastal rock pool mosquito, Aedes togoi, are potential disease vectors present in both East Asia and North America. While their ranges are fairly well-documented in Asia, this is not the case for North America. We used maximum entropy modeling to estimate the potential distributions of Ae. togoi and Ae. j. japonicus in the United States, Canada, and northern Latin America under contemporary and future climatic conditions. Our results suggest suitable habitat that is not known to be occupied for Ae. j. japonicus in Atlantic and western Canada, Alaska, the western, midwestern, southern, and northeastern United States, and Latin America, and for Ae. togoi along the Pacific coast of North America and the Hawaiian Islands. Such areas are at risk of future invasion or may already contain undetected populations of these species. Our findings further predict that the limits of suitable habitat for each species will expand northward under future climatic conditions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2019
Admission routes2
Has abstractyes

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