MétaCan
Menu
Back to cohort
Record W2836783931 · doi:10.1093/jme/tjy104

Evidence for Geographic Variation in Life-Cycle Processes Affecting Phenology of the Lyme Disease Vector Ixodes scapularis (Acari: Ixodidae) in the United States

2018· article· en· W2836783931 on OpenAlexaff
Nicholas H. Ogden, Genevieve Pang, Howard S. Ginsberg, Graham J. Hickling, Russell L. Burke, Lorenza Béati, Jean I. Tsao

Bibliographic record

VenueJournal of Medical Entomology · 2018
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsPublic Health Agency of Canada
FundersU.S. Geological SurveyNational Science Foundation
KeywordsIxodidaeAcariBiologyIxodes scapularisLyme diseaseVector (molecular biology)Geographic variationIxodesParasitiformesZoologyEcologyVirologyDemography

Abstract

fetched live from OpenAlex

The seasonal activity pattern of immature Ixodes scapularis Say (Acari: Ixodidae) varies geographically in the United States, which may affect the efficiency of transmission cycles of pathogens transmitted by this species. To study the factors that determine seasonality, a multiyear study at seven sites across the geographic range of I. scapularis systematically collected questing ticks by flagging/dragging, and feeding ticks by capture of their hosts. The observed phenology patterns were consistent with previous studies reporting geographic variation in seasonal tick activity. Predictions of seasonal activity for each site were obtained from an I. scapularis simulation model calibrated using contemporaneous weather data. A range of scenarios for life-cycle processes-including different regimes of temperature-independent behavioral and developmental diapause, variations in temperature-development rate relationships, and temperature-dependent tick activity-were used in model formulations. These formulations produced a range of simulations of seasonal activity for each site and were compared against the field observed tick data using negative binomial regression models. Best fit scenarios were chosen for each site on the basis of Akaike's information criterion and regression model parameters. This analysis suggests that temperature-independent diapause mechanisms explain some key observed variations in I. scapularis seasonality, and are responsible in part for geographic variations in I. scapularis seasonality in the United States. However, diapause appears to operate in idiosyncratic ways in different regions of the United States, so further studies on populations in different regions will be needed to enable predictive modeling of climatic and climate change effects on I. scapularis seasonal activity and pathogen transmission.

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)0.002
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.045
GPT teacher head0.353
Teacher spread0.307 · 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

Citations85
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical EntomologySame topicViral Infections and VectorsFrench-language works237,207