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Record W3135008336 · doi:10.3389/fvets.2020.605259

A Universal Approach to Molecular Identification of Rumen Fluke Species Across Hosts, Continents, and Sample Types

2021· article· en· W3135008336 on OpenAlexfundno aff
Gillian Mitchell, Ruth N. Zadoks, Philip Skuce

Bibliographic record

VenueFrontiers in Veterinary Science · 2021
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsnot available
FundersAnimal Health and Veterinary Laboratories AgencyScotland’s Rural CollegeQueen's UniversityBiotechnology and Biological Sciences Research CouncilUniversity College DublinUniversity of GlasgowKasetsart UniversityScottish GovernmentUniversiteit UtrechtSlovenská Akadémia Vied
KeywordsBiologyRumenZoologyGenBankHost (biology)EcologyGeneticsGene

Abstract

fetched live from OpenAlex

Rumen fluke are parasitic trematodes that affect domestic and wild ruminants across a wide range of countries and habitats. There are 6 major genera of rumen fluke and over 70 recognized species. Accurate species identification is important to investigate the epidemiology, pathophysiology and economic impact of rumen fluke species but paramphistomes are morphologically plastic, which has resulted in numerous instances of misclassification. Here, we present a universal approach to molecular identification of rumen fluke species, including different life-cycle stages (eggs, juvenile and mature fluke) and sample preservation methods (fresh, ethanol- or formalin-fixed, and paraffin wax-embedded). Among 387 specimens from 173 animals belonging to 10 host species and originating from 14 countries on 5 continents, 10 rumen fluke species were identified based on ITS-2 intergenic spacer sequencing, including members of the genera Calicophoron, Cotylophoron, Fischeroedius, Gastrothylax, Orthocoelium , and Paramphistomum . Pairwise comparison of ITS-2 sequences from this study and GenBank showed >98.5% homology for 80% of intra-species comparisons and <98.5% homology for 97% of inter-species comparisons, suggesting that some sequence data may have been entered into public repositories with incorrect species attribution based on morphological analysis. We propose that ITS-2 sequencing could be used as a universal tool for rumen fluke identification across host and parasite species from diverse technical and geographical origins and form the basis of an international reference database for accurate species identification.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.300
Teacher spread0.270 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations43
Published2021
Admission routes1
Has abstractyes

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