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Record W4367279979 · doi:10.55507/gopzfd.1214396

Molecular Determination of Some Important Viruses Causing Infection in Potato Fields in Turkey

2023· article· en· W4367279979 on OpenAlexaboutno aff
Muhammed Rafiq HAFİZ, Şerife TOPKAYA

Bibliographic record

VenueJournal of Agricultural Faculty of Gaziosmanpasa University · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPotato leafroll virusBiologyVirologyPotato virus XGenBankVirusPhylogenetic treePotato virus YPlant virusVeterinary medicineGeneGeneticsMedicine

Abstract

fetched live from OpenAlex

Potato is one of the most important agricultural crops worldwide and known to be susceptible to more than 40 viruses in nature. In this research, 298 leaf samples collected from potato fields in Afyon, Nevşehir and Bolu provinces in the previous study were used to determine viruses affecting potato production in the region. The leaves of potato plants showing virus symptoms were subjected to RT-PCR using virus-specific primers, in order to detect the presence of Potato leafroll virus (PLRV), Potato virus A (PVA), Potato virus X (PVX) and Potato virus M (PVM). As a result of the study,one or more viruses were detected in 46 (15.43%) of the 298 leaf samples tested. A total of 43 samples infected with PLRV (14.42%) and 3 sample infected with PVX (1.%). It was determined that the most common virus in plant samples collected from Afyon, Nevşehir and Bolu Central regions was PLRV followed by PVX. PVA and PVM were not detected in the samples. The sequences of some positive isolates of PLRV were obtained and used along with the isolates registered in the GenBank to reveal phylogenetic relationships among them. PLRV isolates from Turkey were classified in Group 2 along with isolates from Serbia, Canada, and Pakistan based on phylogenetic analyses.

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: Bench or experimental · Consensus signal: Bench or experimental
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)0.0000.000

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 head0.037
GPT teacher head0.268
Teacher spread0.231 · 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 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
Published2023
Admission routes1
Has abstractyes

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