Mutual Mate Assessment in Wolf Spiders: Differences in the Cues Used by Males and Females
Bibliographic record
Abstract
Abstract When males engage in conspicuous courtship displays, it seems obvious that females would use characteristics of that display in mating decisions. However, males must also have a way to identify and evaluate females prior to engaging in what might be a costly mating ritual. Although it was known that female wolf spiders of the speciesPardosa milvina(Araneae; Lycosidae) attract males using volatile chemical cues, the nature of the cues used by males and females in mate selection had not been investigated. Specifically we determined whether males could detect the mating status of the female and if chemotactile cues from the female played a role in that process. In addition, we quantified conspicuous aspects of the male courtship (leg raises and body shakes) to determine if courtship intensity was related to female choice. Although repeated mating occurred in our studies, males were more likely to court and mate with virgin females. Males used substrate‐borne cues deposited by females to discriminate between mated and virgin females. Females used the conspicuous behaviors of males during courtship, body shakes and leg raises, in mate selection. Thus males and females use different kinds of information and different sensory modalities to assess the suitability of a potential mate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".