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Record W3197983337 · doi:10.1007/978-1-0716-1633-8_5

Silencing of Molecular Targets with Relevance to Insecticide Resistance in Colorado Potato Beetle Using dsRNA.

2022· article· en· W3197983337 on OpenAlexaff
Raed Bouafoura, Mariem Ben Youssef, Pier Morin

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsRNA silencingLeptinotarsaRNA interferenceColorado potato beetleBiologyGene silencingGene knockdownLethalityPEST analysisIntegrated pest managementBiotechnologyRNAGeneticsEcologyBotanyGene

Abstract

fetched live from OpenAlex

Various approaches based on RNA interference (RNAi) have garnered significant attention in the field of insect pest management in recent years. For example, the use of double-stranded RNA (dsRNA) has notably been investigated to target transcripts of interest with relevance to insecticide resistance in multiple pests and has emerged as a potential tool to be deployed in agricultural fields in the near future. A careful characterization of a given dsRNA in a laboratory setting, including the assessment of dsRNA-mediated molecular and phenotypical changes observed in the targeted pest upon dsRNA exposure, is nevertheless essential prior to its use in field-based study. The current chapter thus describes the process via which a dsRNA, aimed at a molecular target underlying insecticide response in the Colorado potato beetle Leptinotarsa decemlineata, is conceived, synthesized and injected. Assessment of knockdown efficiency in injected insects is further presented.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.576

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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 designBench or experimental
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

Citations2
Published2022
Admission routes1
Has abstractyes

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