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Record W2370030595 · doi:10.1094/php-br-15-0052

Re-emergence of <i>Tobacco streak virus</i> Infecting Soybean in the United States and Canada

2016· article· en· W2370030595 on OpenAlexaffabout
Melissa D. Irizarry, Carol L. Groves, Manjula G. Elmore, Carl A. Bradley, Ranjit Dasgupta, Thomas L. German, Douglas J. Jardine, Erika Saalau Rojas, Damon L. Smith, Albert Tenuta, Steven A. Whitham, Daren S. Mueller

Bibliographic record

VenuePlant Health Progress · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of GuelphMinistry of Agriculture, Food and Rural Affairs
Fundersnot available
KeywordsThripsBiologyAgronomyIncidence (geometry)PollenBlightHorticultureBotanyMathematics

Abstract

fetched live from OpenAlex

Tobacco streak virus (TSV) has an extensive plant host range, but until recently has not been a common problem in North American soybean. TSV is associated with bud blight and yield loss due to reduced plant height and density, and delayed seed development and plant maturity. TSV has been reported in recent years in Illinois, Iowa, Kansas, and Wisconsin, as well as Ontario, Canada. Presence of the virus was confirmed by ELISA. In an Iowa field with high incidence, regression analysis indicated a significant positive relationship between incidence and seed moisture. TSV is seed and pollen transmitted, as well as being spread by thrips. Increasingly variable weather creating favorable conditions for thrips may be facilitating the rise of TSV. The combination of increased incidence of TSV with associated potential for yield loss and few known management methods brings attention to the need for further research. Accepted for publication 14 April 2016. Published 26 April 2016.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.296
Teacher spread0.254 · 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 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

Citations11
Published2016
Admission routes2
Has abstractyes

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