Actual and potential distribution of<i>Acrolepiopsis assectella</i>(Lepidoptera: Acrolepiidae), an invasive alien pest of<i>Allium</i>spp. in Canada
Bibliographic record
Abstract
Abstract Acrolepiopsis assectella(Zeller), leek moth, is a widespread and common pest of species ofAlliumL. (Liliaceae) in the western Palaearctic subregion. The establishment ofA. assectellain eastern North America has resulted in economic losses to garlic (Allium sativumL.), leek (Allium porrumL.), and onion (Allium cepaL.) growers, especially to organic producers in eastern Ontario and southern Quebec.Acrolepiopsis assectellawas first recorded in the Ottawa area in 1993. By 2010,A. assectellahad expanded its range into eastern Ontario, southwestern Quebec, Prince Edward Island, and New York. A bioclimate model, using CLIMEX simulation software, was developed to produce mapped results that closely approximated known distributions forA. assectellain central Europe. This model was then validated with recorded distribution records in eastern Europe, Asia, and North America. Model output predicted thatA. assectellawill readily survive in southeastern Canada and the eastern United States of America. Other areas potentially suitable forA. assectellainclude coastal regions of the Pacific Northwest, the interior of southern British Columbia, and north-central Mexico. The continued range expansion ofA. assectellainto otherAllium-growing areas of eastern North America appears to be inevitable. Establishment in these areas presents the risk of substantial production losses toAlliumspp. producers.
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 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".