The Impact of Trap Type and Design Features on Survey and Detection of Bark and Woodboring Beetles and Their Associates: A Review and Meta-Analysis
Bibliographic record
Abstract
A large literature on the survey and detection of forest Coleoptera and their associates exists. Identification of patterns in the effect of trap types and design features among guilds and families of forest insects would facilitate the optimization and development of intercept traps for use in management programs. We reviewed the literature on trapping bark and woodboring beetles and their associates and conducted meta-analyses to examine patterns in effects across guilds and families; we observed the following general patterns: (a) Panel traps were superior to multiple-funnel traps, (b) bark beetles and woodborers were captured in higher numbers in traps treated with a surface treatment to make them slippery than untreated traps, (c) panel and multiple-funnel traps equipped with wet cups outperformed traps with dry cups, (d) black traps were superior to white and clear traps, and (e) purple traps were as good as or superior to green traps for Agrilus spp.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".