Potential distribution and relative abundance of an invasive cereal crop pest, <i>Oulema melanopus</i> (Coleoptera: Chrysomelidae), in Canada
Bibliographic record
Abstract
Abstract Cereal leaf beetle, Oulema melanopus L., is an invasive pest insect of small grain cereal crops, particularly oat, wheat, and barley. The first report of cereal leaf beetle populations in North America came from Michigan in 1962. Surveys indicate that populations have become established throughout eastern North America from Ontario to Alabama and in northwestern North America from Utah to southern British Columbia. The establishment of O. melanopus in western North America has raised concern that its presence is a potential risk to the Canadian cereal industry, especially in the prairie ecozone of western Canada, where up to 10 million hectares of cereal crops are grown annually. Field surveys to date have indicated that O. melanopus has not yet become established in this region. A CLIMEX™ model for O. melanopus in North America was developed, based on climate and ecological parameters, and validated with actual distribution records. The actual distribution of O. melanopus in eastern North America matched the predicted distribution well. The model predicts that, once introduced, O. melanopus would readily survive in the cereal-growing areas of western Canada and present a significant risk to cereal production. The potential for establishment of O. melanopus in the prairie ecozone of western Canada substantiates the efforts by regulatory agencies to prevent accidental introduction of this pest species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".