Measuring trap efficiency for bark beetles (Col., Scolytidae)
Bibliographic record
Abstract
Abstract: The relative efficiency of cylindrical, linear and cross‐barrier traps for trapping bark beetles was investigated based on a theoretical model. Using this model, the effective trap interception area of each trap type was calculated and trap efficiency was defined as the ratio of the effective interception area to the trap surface area. The relative efficiencies of the three trap types were calculated as the ratios of their respective effective interception areas. Based on this approach, assuming random directional movement of dispersing beetles, the order of efficiency of the three trap types, from highest to lowest, was linear, cross‐barrier and cylindrical. The expected ratios of trap catches based on the relative efficiencies of the three trap types were fitted to data from trapping experiments with the mountain pine beetle (Dendroctonus ponderosae Hopkins). In general, there was large variation in trap catches among traps of the same type but the ratios of mean catches per trap conformed to the expected ratios. The results indicate that the model of trap efficiency could be used for designing efficient traps. The methods presented are amenable for assessing the efficiency of other trap designs.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".