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Record W4408054156 · doi:10.1007/s12230-025-09979-5

Responses of Non-Target Arthropods to the dsRNA Bioinsecticide Calantha™ and Conventional Insecticides Targeting Colorado Potato Beetle, Leptinotarsa Decemlineata (Say)

2025· article· en· W4408054156 on OpenAlexaff
Erik J. Wenninger, Samuel P. DeGrey, Jonas K. Insinga, E Knopf, Andrei Alyokhin, Ethann R. Barnes, Ben Bradford, Russell L. Groves, Brian Manley, Julia Piaskowski

Bibliographic record

VenueAmerican Journal of Potato Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsUniversity of FrederictonKimberly-Clark (Canada)
Fundersnot available
KeywordsLeptinotarsaColorado potato beetleBiologyLarvaAgronomyHorticultureToxicologyBotany

Abstract

fetched live from OpenAlex

Abstract Management of the Colorado potato beetle ( Leptinotarsa decemlineata ) is reliant on conventional insecticides that can negatively affect non-target arthropods. Calantha™ (active ingredient: ledprona) is a sprayable double-stranded RNA biopesticide specific for L decemlineata proteasome subunit beta 5 gene that triggers the RNA-interference pathway and is designed to have limited non-target effects. To test this hypothesis, we conducted two years of field trials in Idaho, Wisconsin, and Maine comparing arthropod responses to different insecticide regimes, with and without Calantha, targeting the Colorado potato beetle. Comparisons of arthropod abundance among treatments showed no evidence of effects of Calantha on non-target arthropods, including beneficials (predators, parasitoids), “neutrals” (i.e., non-pests), and other beetle species. Conventional insecticides generally showed more non-target effects, and responses were always stronger for arthropods from vacuum samples than pitfall samples. Insecticide programs featuring Calantha, especially in rotation with other biorational products, may reduce pests while preserving beneficial arthropods and contribute to biological control of arthropod pests in potato fields.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.353
Teacher spread0.336 · 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

Citations16
Published2025
Admission routes1
Has abstractyes

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