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Record W2099256450 · doi:10.7202/706190ar

Serodetection of viruses associated to barley yellow dwarf (BYD) on cereals in Algeria

2005· article· en· W2099256450 on OpenAlexaffvenue
Hadjira Belkahla, Hervé Lapierre

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBarley yellow dwarfDwarfingBiologyRhopalosiphum maidisLuteovirusRhopalosiphum padiSerotypeHordeum vulgareAgronomyPlant virusBotanyVirologyVirusPoaceaePEST analysisHomopteraAphididae

Abstract

fetched live from OpenAlex

Surveys on viruses associated with Barley Yellow Dwarf (BYD) and their vectors were carried out in Algerian cereal areas (Guelma, Constantine, Algiers, Sidi-belabes, Adrar) in 1997 and 1998. Rhopalosiphum padi was present in all zones of culture, whereas R. maidis, Sitobion avenae, S. fragariae and Schizaphis graminum had only local distributions. In most areas BYD-like symptoms, i.e. dwarfing and yellowing of barley ( Hordeum vulgare ), dwarfing and reddening of oat (Avena sativa) and wheat ( Triticum aestivum ), were observed. Serological tests were done on these crops using DAS-ELISA (RMV and SGV) or TAS-ELISA using monoclonal antibodies specifie to CYDV-RPV or using different variant specifie BYDV-PAV (CpA and CpB) and BYDV-MAV monoclonal antibodies. BYDV-PAV was prevalent and few plant samples carrying RMV, SGV, BYDV-MAV or CYDV-RPV were detected. The relative frequencies of BYDV-PAV CpA and CpB serotypes were variable depending on the area and the crop season. The range of symptoms induced on barley by both Algerian BYDV-PAV CpB and BYDV-PAV CpA serotypes was mild to severe. Twenty-one BYDV-MAV isolates were compared using monoclonal antibodies, which distinguish two serotypes of this virus. Only one serotype was detected. This same serotype is also the most prevalent in Europe.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.047
GPT teacher head0.279
Teacher spread0.232 · 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

Citations5
Published2005
Admission routes2
Has abstractyes

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