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Record W4402326442 · doi:10.1093/jee/toae191

Failure of a mass trapping method against the striped cucumber beetle (Coleoptera: Chrysomelidae) in organic cucurbit fields

2024· article· en· W4402326442 on OpenAlexafffund
Jessee Tinslay, Marc Fournier, Isabelle Couture, Pierre Lafontaine, Maxime Lefevbre, Éric Lucas

Bibliographic record

VenueJournal of Economic Entomology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsInstitut de Recherche et de Développement en AgroenvironnementCentre de Recherche Industrielle du QuébecMinistère de l'Agriculture, des Pêcheries et de l'AlimentationUniversité du Québec à Montréal
FundersUniversité du Québec à Montréal
KeywordsSemiochemicalBiologyTrappingAgronomyToxicologyHorticultureEcologyPEST analysis

Abstract

fetched live from OpenAlex

The striped cucumber beetle (SCB) Acalymma vittatum (F.) is one of the most important pests in North American cucurbit crops. While conventional chemical control methods are usually effective in controlling SCB populations, few alternative control methods are available for organic cucurbit crops. The goal of the present study was to evaluate an optimized mass trapping system using yellow traps baited with a floral-based semiochemical. More specifically, the objectives were to determine if the trapping method could (i) significantly reduce SCB populations and (ii) maintain these populations below the economic threshold throughout the growth season within organic cucurbit crops. The method did not reduce nor maintain the SCB populations below the economic threshold of one SCB per plant. Possible hypotheses explaining the diverging results are discussed.

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 score0.792
Threshold uncertainty score0.944

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 science0.0000.000
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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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
Published2024
Admission routes2
Has abstractyes

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