Conspecific females promote calling behavior in the noctuid moth, <i><scp>P</scp>seudaletia adultera</i>
Bibliographic record
Abstract
Abstract Changes in female calling behavior in response to the presence of conspecific pheromones (pheromone autodetection) have been demonstrated in a number of moth species. However, the observed changes vary between species, and several ecological and adaptive explanations for autodetection have been proposed. We studied the effect of conspecific females on the calling behavior of the noctuid moth Pseudaletia adultera (Schaus) (Lepidoptera: Noctuidae, Hadenini), by comparing the age of first calling, as well as the onset and pattern of calling, when females were held individually or in the presence of conspecifics. Grouped females started calling at a lower age, a higher percentage of females called during the scotophase, and they called longer compared to females held in isolation. We also demonstrated that female antennae respond to each of the three main components of the sex pheromone – (Z)‐11‐hexadecen‐1‐ol, (Z)‐11‐hexadecen‐1‐yl acetate, and (Z)‐11‐hexadecenal – and that the response patterns differed from those of male antennae. By calling more and extending her calling window in presence of conspecific females, a female may increase her chances of accessing males. However, the potential benefits need to be considered within an ecological context, considering factors such as migration, oviposition, and foraging.
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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) | 0.002 | 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".