Comparative efficacy of five types of trap for woodborers in the Cerambycidae, Buprestidae and Siricidae
Bibliographic record
Abstract
Summary 1 Traps of four new designs were tested against the conventionally used multiple‐funnel trap to determine whether trapping of large wood‐boring insects can be improved in western Canada. All four new traps used a large collecting receptacle containing detergent‐laced water, and three presented a prominent visual silhouette above the receptacle. 2 In total, 27 336 large woodborers were captured from 10 June to 30 September in an experiment in the southern interior of British Columbia, and 4737 from 6 June to 27 July in an experiment in northern Alberta. The woodborers captured in the British Columbia experiment were mainly beetles in the families Cerambycidae (79%) and Buprestidae (15%), and woodwasps in the family Siricidae (6%). Most woodborers, e.g. three Monochamus spp. and Xylotrechus longitarsus (the predominant cerambycids), were captured throughout the summer, with peak captures in August. 3 Cross‐vane, pipe and stacked‐bottomless‐flower‐pot traps were generally superior to pan and multiple‐funnel traps for insects in nine taxa, but cross‐vane traps were the most effective overall, trapping 32% of all insects captured. 4 The large number of target insects captured in a relatively small number of traps in the two experiments suggests that employment of an efficacious trap with a large vertical silhouette and a wide, escape‐proof collecting receptacle could make mass trapping of large woodborers in timber processing areas operationally feasible. 5 Because the most effective traps were unstable in the wind, and the detergent‐laced water captured unacceptably high numbers of small mammals, design modifications are necessary. We are currently developing a wind‐firm trap, with a prominent vertical silhouette, a wide collecting surface, and an escape‐proof, but dry collecting receptacle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".