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Record W4210903970 · doi:10.1093/jme/tjac001

Modeling Geographic Uncertainty in Current and Future Habitat for Potential Populations of <i>Ixodes pacificus</i> (Acari: Ixodidae) in Alaska

2022· article· en· W4210903970 on OpenAlexaboutno aff
Frank D. W. Witmer, Timm W. Nawrocki, Micah B. Hahn

Bibliographic record

VenueJournal of Medical Entomology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Institutes of Health
KeywordsIxodidaeAcariBiologyIxodesEcologyHabitatParasitiformesZoologyTick

Abstract

fetched live from OpenAlex

Ixodes pacificus Cooley & Kohls is the primary vector of Lyme disease spirochetes to humans in the western United States. Although not native to Alaska, this tick species has recently been found on domestic animals in the state. Ixodes pacificus has a known native range within the western contiguous United States and southwest Canada; therefore, it is not clear if introduced individuals can successfully survive and reproduce in the high-latitude climate of Alaska. To identify areas of suitable habitat within Alaska for I. pacificus, we used model parameters from two existing sets of ensemble habitat distribution models calibrated in the contiguous United States. To match the model input covariates, we calculated climatic and land cover covariates for the present (1980-2014) and future (2070-2100) climatologies in Alaska. The present-day habitat suitability maps suggest that the climate and land cover in Southeast Alaska and portions of Southcentral Alaska could support the establishment of I. pacificus populations. Future forecasts suggest an increase in suitable habitat with considerable uncertainty for many areas of the state. Repeated introductions of this non-native tick to Alaska increase the likelihood that resident populations could become established.

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)0.000
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 score0.135
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0040.000

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 head0.027
GPT teacher head0.293
Teacher spread0.267 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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