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Record W4379520375 · doi:10.3390/ijms24119755

RNA Interference Past and Future Applications in Plants

2023· review· en· W4379520375 on OpenAlexafffund
Sarah Koeppe, L. M. Kawchuk, Melanie Kalischuk

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsRNA silencingRNA interferenceTrans-acting siRNARNARNA-induced silencing complexGene silencingBiologyRNA-induced transcriptional silencingSmall hairpin RNAGeneticsSmall interfering RNAGeneComputational biology

Abstract

fetched live from OpenAlex

Antisense RNA was observed to elicit plant disease resistance and post-translational gene silencing (PTGS). The universal mechanism of RNA interference (RNAi) was shown to be induced by double-stranded RNA (dsRNA), an intermediate produced during virus replication. Plant viruses with a single-stranded positive-sense RNA genome have been instrumental in the discovery and characterization of systemic RNA silencing and suppression. An increasing number of applications for RNA silencing have emerged involving the exogenous application of dsRNA through spray-induced gene silencing (SIGS) that provides specificity and environmentally friendly options for crop protection and improvement.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.999
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.369
Teacher spread0.278 · 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 designOther design
Domainnot available
GenreReview

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

Citations64
Published2023
Admission routes2
Has abstractyes

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