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Record W1550527260 · doi:10.5772/14298

Detection, Understanding and Controlof Soybean Mosaic Virus

2011· book-chapter· en· W1550527260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsSoybean mosaic virusMosaicBiologyMosaic virusVirologyPlant virusVirusGeographyPotyvirus

Abstract

fetched live from OpenAlex

Among 67 or so viruses that are able to infect soybean, 27 are considered a threat to the soybean industry Soybean mosaic virus (SMV) is the most prevalent virus and is recognized as the most serious, long-standing problem in many soybean producing areas in the world SMV is a member of the genus Potyvirus in the family Potyviridae. The disease caused by SMV was first documented in the USA in 1915 by Since then, the virus has been found in China, Japan, South Korea, Canada, Bazil, Australia and many other countries wherever soybean is grown. Infection by SMV usually results in severe yield losses and seed quality reduction. It has been reported that yield losses usually range from 8 to 50% under natural field conditions Since SMV is a seed-borne viral pathogen and aphids can efficiently spread it from plant to plant while they feed, it is difficult to control the virus and produce SMV-free seeds. Furthermore, SMV often infects soybeans with other viruses such as Bean pod mottle virus (BPMV), Alfalfa mosaic virus (AMV) and Tobacco ringspot virus (TRSV) Such synergistic infections with two or more viruses cause much more severe damages than infection by each virus alone Utilization of soybean cultivars resistant to SMV is considered the most effective way of controlling the diseases. Extensive screening for soybean gemplasm resistant to SMV has resulted in the identification of three independent resistant genes, i.e.,

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.

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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score0.453

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 head0.091
GPT teacher head0.247
Teacher spread0.156 · 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