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Record W3200005666 · doi:10.1080/07060661.2021.1977999

Potential of resistance inducers for soybean rust management

2021· article· en· W3200005666 on OpenAlexvenueno aff
Samuel de Paula, Sabrina Holz, Dablieny Héllen Garcia Souza, Sérgio Florentino Pascholati

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsPhakopsora pachyrhiziSoybean rustRust (programming language)Resistance (ecology)BiologyBiotechnologyPesticideInducerAgronomyFungicideComputer science

Abstract

fetched live from OpenAlex

The induction of resistance is an important strategy in integrated plant disease management. This strategy has a great potential to be adopted by farmers, motivated by the worldwide demand for a reduced pesticide use in food production. Studies have shown that resistance inducers are effective against a wide variety of pathogens, including Phakopsora pachyrhizi, the causal agent of Asian soybean rust. This review aims to synthesize current knowledge on the use of induced resistance for soybean rust management. Special emphasis is placed on commercially available products and potential resistance inducers described in the literature. Finally, perspectives and challenges regarding the use of resistance inducers for soybean rust management are highlighted.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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

Citations21
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Plant PathologySame topicYeasts and Rust Fungi StudiesFrench-language works237,207