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Record W2899792443 · doi:10.5539/jas.v10n12p426

Metabolic Resistance in the Fall Armyworm: An Overview

2018· article· en· W2899792443 on OpenAlexvenueno aff
Indyra F. Carvalho, Larissa L. Erdmann, Larissa Longaray Machado, A. P. S. A. da Rosa, Moisés João Zotti, Camila G. Neitzke

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyFall armywormContext (archaeology)SpodopteraResistance (ecology)Abiotic componentBiotechnologyDetoxification (alternative medicine)EcologyBiochemistryGene

Abstract

fetched live from OpenAlex

The Fall Armyworm (FAW), Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae), is one of the most important pests in the American continent and has recently become an invasive species in Africa. It’s main form of control is through the use of insecticides, however during the last 40 years, due to continuous spraying and high doses used along with FAW’s high adaptative capacity, developed resistance to different classes of chemical insecticides. One of the main mechanisms enabling resistance in the FAW is by detoxification enzymes or so-called metabolic resistance. P450s, Carboxylesterases and Glutathione-S-Transferases are the main families of enzymes believed to mediate the detoxification process. These enzymes in the FAW, although widely studied, have been difficult to generalize into patterns. This happens mainly because FAW populations can have high genetic variability within the species, as they have different biotypes meaning that they can be morphologically identical but physiologically different and consequently, enzymatic responses to toxic compounds can also differ. There are also differences due to the diversity of biomes in which S. frugiperda is found, which due to adaptations to different host plants and other abiotic factors, it’s hard to predict enzymatic responses in insecticide resistance. In this context we aimed to review the literature regarding these three main enzymes families involved in metabolic resistance in S. frugiperda, by cataloguing, analysing and summarizing these studies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.154

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 head0.019
GPT teacher head0.287
Teacher spread0.269 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

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