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Record W2809337702 · doi:10.1080/07060661.2018.1490929

Molecular characterization of ageratum enation virus and DNA-satellites associated with yellowing and leaf curl symptoms on mulberry in Pakistan

2018· article· en· W2809337702 on OpenAlexvenueno aff
Muhammad Naeem Sattar, Fasiha Qurashi, Zafar Iqbal, Muhammad Saleem Haider

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBegomovirusBiologyGeminiviridaeLeaf curlWhiteflyBotanyclone (Java method)Plant virusVirusVirologyGene

Abstract

fetched live from OpenAlex

The whitefly-transmitted begomoviruses (family Geminiviridae) infect dicotyledonous plants and occur in tropical and sub-tropical regions. Although most commonly found in herbaceous plants, recently begomoviruses have increasingly been identified in woody plants. Leaf samples from five mulberry (Morus alba L.) plants with leaf yellowing and curling symptoms were collected in Lahore (Pakistan) and shown by PCR to be associated with a begomovirus, an alphasatellite and a betasatellite. The complete sequences of two begomovirus clones, as well as an alphasatellite clone and a betasatellite clone, were determined. The begomovirus clones were shown to be isolates of ageratum enation virus (AEV), a virus most commonly identified in weeds but increasingly being identified in crops such as tomato, soybean and fenugreek. Analyses of the sequences of the alphasatellite and betasatellite clones showed them to be isolates of Guar leaf curl alphasatellite and Papaya leaf curl betasatellite, respectively. Both the virus and the alphasatellite sequences showed evidence of a recombination. This is the first report of the weed-infecting monopartite begomovirus AEV, and associated satellites, infecting the woody plant mulberry.

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 score0.007
Threshold uncertainty score0.014

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.228
Teacher spread0.214 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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