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Record W4409885273 · doi:10.1093/jee/toaf055

Isocycloseram seed treatment for reducing wireworm populations (<i>Agriotes obscurus</i>) (Coleoptera: Elateridae) and protecting wheat crops in British Columbia

2025· article· en· W4409885273 on OpenAlexaffabout
Willem G. van Herk, Robert S. Vernon

Bibliographic record

VenueJournal of Economic Entomology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsNative Mental Health Association of CanadaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyAgronomyCropSowingAbiotic componentTillageEcology

Abstract

fetched live from OpenAlex

Wireworms (Coleoptera: Elateridae), the larval stage of several economic click beetle species, have become major cereal crop pests in key agricultural regions of Canada and the United States. In recent trials following minimum tillage practices (Alberta), we determined that isocycloseram, the initial isoxazoline agricultural seed treatment developed, provided exceptional control of cereal crop damage, and significantly reduced neonate and resident wireworm populations of the sugarbeet wireworm, Limonius californicus (Mannerheim). Herein we evaluated isocycloseram in cultivated wheat plots (British Columbia) for control of the dusky wireworm, Agriotes obscurus L., and collectively these studies determined that isocycloseram applied at 5.0 to 7.5 g AI/100 kg seed protected crop stand and yield from these species equal to all currently registered wireworm seed-treatment insecticides (ie, neonicotinoids, diamides, and meta-diamides), and significantly reduced resident and neonate wireworms equal to levels expected from the former industry standard lindane. Abiotic and biotic conditions negatively influencing insecticide performance and ways to mitigate them were also identified. These conditions include soil fertility, moisture, and compaction, and planting after most wireworm feeding in the spring has occurred.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.911

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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 designObservational
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

Citations3
Published2025
Admission routes2
Has abstractyes

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