Olfactory responses of the omnivorous generalist predator <i>Dicyphus hesperus</i> to plant and prey odours
Bibliographic record
Abstract
Abstract Responses of female Dicyphus hesperus Knight (Heteroptera: Miridae) to the odours of plants and prey were tested in the laboratory using a Y‐tube olfactometer. Females were attracted to the odour of tomato leaves infested with nymphs of the greenhouse whitefly, Trialeurodes vaporariorum Westwood (Homoptera: Aleyrodidae), compared to uninfested leaves. No such attraction occurred to tomato leaves infested with two‐spotted spider mites, Tetranychus urticae Koch (Acari: Tetranychidae). When females were simultaneously presented with the odours of whitefly and mite‐infested leaves, no preference for either odour was recorded. Similarly, females were attracted to the odour of pepper leaves infested with green peach aphids [Myzus persicae (Sulzer) (Homoptera: Aphididae)] compared to uninfested leaves, but were not attracted to the odour of pepper leaves infested with eggs of cabbage loopers, Trichoplusia ni (Hübner) (Lepidoptera: Noctuidae). When aphid‐infested and looper‐egg‐infested pepper leaves were presented simultaneously, no preference for either odour was detected. The results are discussed as they relate to the evolution of infochemical use in generalist omnivorous predators.
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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".