Asian Longhorned Beetle (Coleoptera: Cerambycidae), an Introduced Pest of Maple and Other Hardwood Trees in North America and Europe
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Asian longhorned beetle, Anoplophora glabripennis (Motschulsky), threatens urban and forest hardwood trees both where introduced and in parts of its native range. Native to Asia, this beetle has hitchhiked several times in infested wood packaging used in international trade, and has established breeding populations in five U.S. states, Canada, and at least 11 countries in Europe. It has a broad host range for a cerambycid that attacks living trees, but in the introduced ranges it prefers maples. Identification, classification, and life history of this insect are reviewed here. Eradication is the goal where it has been introduced, which requires detection of infested trees using several approaches, including ground and tree-climbing surveys. Several agencies and researchers in the United States and Europe are evaluating the use of pheromone- and kairomone-baited traps. Control options beyond cutting down infested trees are limited. To date, the parasitoids and predators of this beetle have broad host ranges and are unlikely to be approved in the United States or Europe. An effective delivery system under development for entomopathogenic fungi appears promising. Systemic insecticides have been widely used in the United States, but the ability of these chemicals to reach lethal doses in the crown of large trees is disputed by some scientists, and the potential nontarget effects, especially on pollinators, raise concerns. The most practical approach for eradicating Asian longhorned beetle is to optimize trapping methods using semiochemicals for early detection to eliminate the insect before it spreads over large areas.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it