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Record W2901434006 · doi:10.1017/s0031182018001907

Genetic and morphometric categorization of<i>Taenia ovis</i>from Sheep in Iran

2018· article· en· W2901434006 on OpenAlexaff
Sima Rostami, Reza Salavati, Robin N. Beech, Zahra Babaei, Mitra Sharbatkhori, Saeedeh Shamsaddini, Saeid Nasibi, Majid Fasihi Harandi

Bibliographic record

VenueParasitology · 2018
Typearticle
Languageen
FieldMedicine
TopicParasitic infections in humans and animals
Canadian institutionsMcGill University
Fundersnot available
KeywordsOvisBiologyHaplotypePhylogenetic treeBreedVeterinary medicineCladeRibosomal RNAMitochondrial DNAZoologyGenetic variationNucleotide diversityGeneticsGeneGenotypeEcology

Abstract

fetched live from OpenAlex

Little is known about the genetic and morphological characters of Taenia ovis. The purpose of the present study was to characterize sheep isolates of T. ovis using rostellar hook morphometry as well as mitochondrial genes sequence analysis. Ninety sheep specimens of Cysticercus ovis were collected from 18 slaughterhouses in Iran. The mean ± s.d. for total length of large and small hooks were 174.1 ± 6.4 and 116.7 ± 5.4 µm, respectively. CO1 and 12S rRNA sequence analysis showed 11 and nine haplotypes, respectively. The level of pairwise nucleotide variations between individual haplotypes of CO1 and 12S rRNA genes were 0.3-1.1 and 0.2-1.0%, respectively. Level of nucleotide variation in CO1 and 12S rRNA between T. ovis haplotypes from present study and eight other Taenia species was found to be 11.3-17.8 and 5.3-16.3%, respectively. Phylogenetic analysis clustered all T. ovis isolates into a single clade comprised of the all CO1 and 12S rRNA haplotypes. CO1 nucleotide difference between T. ovis ovis and T. asiatica was 13.6% that is lesser than the corresponding difference between T. ovis ovis and T. ovis krabbei, warranting the designation of two separate species as T. ovis and T. krabbei. Interclass correlation coefficients showed that there was no significant association between rostellar hook length variation and the variability of the mitochondrial genes.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.023
GPT teacher head0.328
Teacher spread0.305 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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