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Record W1973475770 · doi:10.1017/s0022149x15000176

Molecular evidence shows that the liver fluke <i>Fasciola gigantica</i> is the predominant <i>Fasciola</i> species in ruminants from Pakistan

2015· article· en· W1973475770 on OpenAlexafffund
Umer Chaudhry, Bradley van Paridon, Muhammad Zubair Shabbir, Muhammad Shafee, Kamran Ashraf, Tahir Yaqub, John S. Gilleard

Bibliographic record

VenueJournal of Helminthology · 2015
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsUniversity of LethbridgeUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFasciolaFasciola hepaticaFasciola giganticaBiologyLiver flukeHepaticaInternal transcribed spacerLivestockVeterinary medicineZoologyParasitic diseaseHelminthsEcologyDiseaseRibosomal RNAPathologyGeneticsGene

Abstract

fetched live from OpenAlex

Fascioliasis is an important disease affecting livestock, with great costs to producers worldwide. It has also become a serious issue for human populations in some endemic areas as an emerging zoonotic infection. There are two Fasciola species of liver fluke responsible for this disease, which occur worldwide, Fasciola hepatica and Fasciola gigantica. Identifying these two species on the basis of adult or egg morphology requires specialist knowledge due to the similarity of characters, and may misidentify putative intermediate or hybrid forms. In this study we sequenced the internal transcribed spacer 2 (ITS-2) rDNA of liver flukes collected from multiple species of hosts from seven localities in the Punjab and Baluchistan provinces of Pakistan, to determine the distribution of these two species. All 46 flukes processed in this study, collected from seven sites, showed the rDNA ITS-2 genotype corresponding to F. gigantica, contradicting previous reports, based on adult and egg morphology, that both species are present in Pakistan, with F. hepatica being the more common.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.119
GPT teacher head0.348
Teacher spread0.228 · 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 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

Citations26
Published2015
Admission routes2
Has abstractyes

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