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Record W1990368379 · doi:10.1094/pd-90-0723

Widespread Occurrence of <i>Wheat spindle streak mosaic virus</i> in Belgium

2006· article· en· W1990368379 on OpenAlexaboutno aff
Céline Vaïanopoulos, Anne Legrève, Cristóbal Molina Lorca, Virginie Moreau, Stéphan Steyer, Henri Maraite, Claude Bragard

Bibliographic record

VenuePlant Disease · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersWaalse Gewest
KeywordsBiologyVirusVirologyPlant virusPolymerase chain reactionSYBR Green IMosaic virusInoculationReverse transcription polymerase chain reactionReal-time polymerase chain reactionCultivarHorticultureGeneticsGeneMessenger RNA

Abstract

fetched live from OpenAlex

In order to assess the occurrence of Wheat spindle streak mosaic virus (WSSMV) in Belgium, a reverse-transcription polymerase chain reaction (RT-PCR) was developed, targeting WSSMV isolates from Canada, France, Germany, Italy, and the United States. The primers also were designed for virus quantification by real-time RT-PCR with SYBR-Green. No cross-reaction with soilborne cereal viruses such as Barley mild mosaic virus, Barley yellow mosaic virus, Soilborne cereal mosaic virus, and Soil-borne wheat mosaic virus was observed. The RT-PCR and real-time quantitative RT-PCR allowed a more sensitive detection of WSSMV than enzymelinked immunosorbent assay. The incidence of WSSMV in Belgium was evaluated using a bioassay with wheat cvs. Cezanne and Savannah and rye cv. Halo, grown in 104 Belgian soils. The presence of WSSMV was detected from plants grown in 32% of the soils. The RT-PCR methods developed here, combined with large sampling, allowed WSSMV to be detected for the first time in Belgium. The real-time quantitative RT-PCR was developed as a tool for evaluating the resistance to WSSMV by quantifying the virus concentration in wheat cultivars.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.593

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 head0.022
GPT teacher head0.236
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 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

Citations20
Published2006
Admission routes1
Has abstractyes

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