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Record W4285130525 · doi:10.5267/j.ccl.2022.4.003

Insecticidal bioefficacy screening of some chalcone and acetophenone hydrazone derivatives on Spodopetra Frugiperda (Lepidoptera: Noctuidae)

2022· article· en· W4285130525 on OpenAlexvenueno aff
Yousry A. Ammar, Ali M. Drar, Mohamed A. Gad

Bibliographic record

VenueCurrent Chemistry Letters · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsNoctuidaeLepidoptera genitaliaHydrazoneSpodopteraChalconeChemistryPEST analysisToxicologyStereochemistryBotanyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Spodopetra Frugiperda is a highly polyphagous migratory lepidopteran pest species. It causes infestation in crops leading to severe crop losses. Being a new invasive parasite, its susceptibility to insecticides needs to be explored and therefore, there is an urgent need to develop the potent insecticides for the effective control of this insect pest. This is the first report on toxic effects produced by the prepared chalcone and hydrazone analogs, followed by structure relationships. Five compounds of chalcone and hydrazone derivatives have been synthesized in pure state as reported procedures, and their toxicity as potential insecticidal agent against Spodopetra Frugiperda was screened. Their characterizations by using spectroscopic analyses were performed. The toxicity data exhibited that compound 5 is more toxic about 2-fold than other synthesized compounds, the other screened compounds showed weak to strong toxicological activity against Spodopetra Frugiperda (lepidoptera: Noctuidae).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.241
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 source (direct Gemma or distilled Codex), 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

Citations31
Published2022
Admission routes1
Has abstractyes

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