Developing techniques for monitoring forest tent caterpillar populations using synthetic pheromones
Bibliographic record
Abstract
Abstract To effectively monitor forest tent caterpillar, Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae), populations using sex pheromone baited traps, we field-tested pheromone dispenser (lure) type, lure age, and trap design using (Z,E)-5,7-dodecadienal:(Z,Z)-5,7-dodecadienal (100:1). Rubber septa lures, polyurethane lures, and two trap types [sticky-type pheromone traps (Wing Trap I) and bucket-type pheromone traps (Universal Moth trap)] were evaluated. Traps baited with polyurethane lures produced higher trap catches and lower zero-catch frequencies than did rubber septa traps. There was no detectable difference in trap catch among polyurethane lures aged 0–28 days. Wing traps reached a functional saturation point in outbreak M. disstria populations and caught fewer moths than Universal traps in nonoutbreak populations. A nonsaturating trap such as the Universal trap in conjunction with the polyurethane lure should be effective for monitoring M. disstria populations.
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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) | 0.000 | 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".