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Record W2124042478 · doi:10.1017/s0022149x12000612

Predicting the potential distribution of<i>Vexillata</i>(Nematoda: Ornithostrongylidae) and its hosts (Mammalia: Rodentia) within America

2012· article· en· W2124042478 on OpenAlexaff
Elizabeth A. Martínez-Salazar, Tania Escalante, Miguel Linaje, Jorge Falcón-Ordáz

Bibliographic record

VenueJournal of Helminthology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyNearctic ecozoneEcologyBiogeographyRange (aeronautics)Host (biology)Species distributionWildlifeHabitatZoologyParasite hostingNematodeDistribution (mathematics)PhylogeographyGenusPhylogenetics

Abstract

fetched live from OpenAlex

Species distribution modelling has been a powerful tool to explore the potential distribution of parasites in wildlife, being the basis of studies on biogeography. Vexillata spp. are intestinal nematodes found in several species of mammalian hosts, such as rodents (Geomyoidea) and hares (Leporidae) in the Nearctic and northern Neotropical regions. In the present study, we modelled the potential distribution of Vexillata spp. and their hosts, using exclusively species from the Geomyidae and Heteromyidae families, in order to identify their distributional patterns. Bioclimatic and topographic variables were used to identify and predict suitable habitats for Vexillata and its hosts. Using these models, we identified that temperature seasonality is a significant environmental factor that influences the distribution of the parasite genus and its host. In particular, the geographical distribution is estimated to be larger than that predicted for its hosts. This suggests that the nematode has the potential to extend its geographical range and also its spectrum of host species. Increasing sample size and geographical coverage will contribute to recommendations for conservation of this host-parasite system.

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 score0.104
Threshold uncertainty score0.998

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)0.0030.000

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 head0.014
GPT teacher head0.246
Teacher spread0.233 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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