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Record W2949637167 · doi:10.3389/fpls.2019.00866

Editorial: Plant Responses to Phytophagous Mites/Thrips and Search for Resistance

2019· editorial· en· W2949637167 on OpenAlexafffund
Raul Antônio Sperotto, Vojislava Grbić, Maria L. Pappas, Kirsten A. Leiss, Merijn R. Kant, CR Wilson, M. Estrella Santamaría, Yulin Gao

Bibliographic record

VenueFrontiers in Plant Science · 2019
Typeeditorial
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaAlexander S. Onassis Public Benefit FoundationFundação de Amparo à Pesquisa do Estado do Rio Grande do SulConselho Nacional de Desenvolvimento Científico e TecnológicoStichting voor de Technische WetenschappenNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsThripsBiologyResistance (ecology)BotanyHorticultureAgronomy

Abstract

fetched live from OpenAlex

Phytophagous mites and thrips are global pests affecting a wide range of agricultural crops (Mouden et al., 2017; Agut et al., 2018). Among the arthropods, they are phylogenetically distant, but both classes harbor species ranging from highly specialized to extremely polyphagous (Rioja et al., 2017; Wu et al., 2018). Through convergent evolution, mites and thrips evolved stylets to facilitate feeding from mesophyll or epidermal cells (Bensoussan et al., 2016; Rioja et al., 2017; Wu et al., 2018). Despite large crops losses (Agut et al., 2018; Steenbergen et al., 2018) that are expected to become more severe with global warming (Ximenez-Embún et al., 2017; Urbaneja-Bernat et al., 2019), the interactions between mites/thrips and their host plants have been understudied. Hence, understanding how plants defend themselves against these pests is essential for developing crop protection strategies. This Research Topic provides an update on recent advances in the plant molecular and physiological mechanisms associated with phytophagous mite/thrips-plant interactions, and provides an overview of different approaches for improving crop resistance sustainably, either through repellence, feeding disruption or prevention of feeding damage. Here, we highlight some of the major points arising from these reports.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.017
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations6
Published2019
Admission routes2
Has abstractyes

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