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Record W4407879160 · doi:10.1139/cjps-2024-0177

Bioclimatic analysis of cabbage seedpod weevil, <i>Ceutorhyncus obstrictus</i> (Marsham) (Coleoptera: Curculionidae) and canola, <i>Brassica napus</i> Linnaeus (Brassicaceae) responses to climate

2025· article· en· W4407879160 on OpenAlexaffvenueabout
R.M. Weiss, Tim Haye, O. Olfert, Shelley Barkley, John Gavloski, James A. Tansey, Jennifer Otani, Meghan A. Vankosky

Bibliographic record

VenueCanadian Journal of Plant Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsSaskatchewan Ministry of AgricultureAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCanolaCurculionidaeWeevilBrassicaBrassicaceaeBiologyAgronomyBotanyGlucosinolate

Abstract

fetched live from OpenAlex

The cabbage seedpod weevil (CSW), Ceutorhynchus obstrictus (Marsham) (Coleoptera: Curculionidae) is an important pest of brassicaceous crops, including canola ( Brassica napus Linnaeus). CSW consumes seeds of its host from inside the developing pods. It was introduced to North America from Europe and now occurs throughout the United States of America and Canada. Climate is one of the most important factors that determines species distribution and abundance. CLIMEX is a bioclimate model development application. Based on climate inputs, bioclimatic simulation models are tools that predict the potential geographic distribution and abundance of insects and plants. This study updated a previous bioclimatic model for CSW and presents a new model for canola. Validated models were used to conduct bioclimatic analysis of both species, the results of which provide a better understanding of how climate affects spatial distribution and abundance of CSW and the distribution and yield of canola. Application of incremental temperature and moisture scenarios were used to predict the spatial relationship of CSW risk and canola yield. We anticipate that the canola model will be applied to future bioclimatic studies of pests and beneficial insects of canola. Both the CSW and canola model can be used in climate change studies using datasets for predicted future climates.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

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)0.0000.000

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

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