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Record W1937479588 · doi:10.6000/1927-5129.2015.11.49

Detection of Grapevine Fanleaf Virus Using Serological and Biological Assays

2015· article· en· W1937479588 on OpenAlexvenueno aff
Gülcan Tarla, Mehmet Yilmaz

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyNicotiana benthamianaVirusSerologyCucumisVirologyChenopodium quinoaPlant virusBotanyHorticultureAntibody

Abstract

fetched live from OpenAlex

The production of grapevine is important agricultural sector in Turkey. But, the production is lower than the other Mediterranean countries. One of the main reasons of low yield is many viruses’ diseases. The nepoviruse diseases are responsible for significant lossesin vineyards. Grapevine fanleaf virus (GFLV) is the most important deadly virus among them. It is transmitted by graft and vector nematodes. It has not been studied enough about this virus in our country. There is not enough detailed research on this virus in our country. In this study, the maintenance of GFLV in vineyards and their occurrence areas were determined in Adana and Mersin provinces by serological and biological assays. Out of total 384 grapevine samples, 63 plants (16.4%) were found to be infected with GFLV by double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA). In addition to this, as herbaceous indicator plants; Nicotiana benthamiana Domin., N. tabacum L., N. rustia L., Chenopodium amaranthicolor Coste et Reyn., C. quinoa Wild., Cucumis sativus L., and Gomprena globosa L. were used in biological assays. But chloroticlocallesions were observed only on Nicotiana benthamiana Domin. among weedy indicator plants by mechanical transmission.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.150
GPT teacher head0.302
Teacher spread0.152 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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