Mark–recapture of <i>Agriotes obscurus</i> and <i>Agriotes lineatus</i> with dense arrays of pheromone traps in an undisturbed grassland population reservoir
Bibliographic record
Abstract
Abstract The present study was conducted using mark–released populations of male Agriotes obscurus ( AO ) and Agriotes lineatus ( AL ) adults to simulate the spatial and temporal capture rates of wild beetle populations in dense arrays of pheromone traps in a confined, nonfarmed habitat. Two parallel rows of traps, spaced 3 m apart along corridors of grassy dyke, recaptured 85.6% of AO and 77.8% of AL with arrays of their respective pheromone traps, mostly within the first week of release. In arrays of mixed AO and AL traps, recapture rates were 77.8% and 83.3%, respectively. In arrays with only AO traps, 31.2% of AL males released within the arrays mistakenly entered the AO traps, which declined to only 2.2% when released in arrays with both AO and AL traps. In arrays with only AL traps, only 0.7% of released AO were mistakenly taken in the AL traps, and only 0.3% mistakenly entered AL traps in mixed AO and AL trap arrays. Between 34.4–38.9% of AO and 21.1–25.6% of AL released in areas immediately adjacent to the trapping arrays were caught, mostly in the outermost traps. The implications of these results for determining the efficacy of mass trapping 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) | 0.000 | 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 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".