Mass trapping wild <i>Agriotes obscurus</i> and <i>Agriotes lineatus</i> males with pheromone traps in a permanent grassland population reservoir
Bibliographic record
Abstract
Abstract A study was conducted to determine whether arrays of pheromone traps could be used to reduce populations of male Agriotes obscurus ( AO ) and Agriotes lineatus ( AL ) adults in a confined nonfarmed habitat (grassy dyke). Traps placed 3 m apart in 15 × 2 arrays captured significantly more AL than AO , although the trap catch varied with location for both species and was inversely related to the number of nearby competing traps. Models of beetle movement indicated that a considerable proportion of males ( AL : 18.4–71.8%; AO : 35.0–58.3%) collected in the arrays had moved in from elsewhere and that AL beetles are more active than AO beetles . AL beetles frequently entered AO traps unless both trap types were present in the array, whereas AO rarely entered AL traps. Concurrent catches in pitfall traps placed inside and outside pheromone trapping zones indicated the trap arrays significantly reduced male (but not female) AO and AL beetles inside their respective arrays, that AO traps reduced AL beetles in AO arrays, and that both AL and AO traps could potentially reduce the number of mating pairs in these arrays. The implications of these results in determining the efficacy of this approach as a click beetle management approach are discussed.
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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 | 0.000 | 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) | 0.001 | 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".