Relationship Between Condition, Aggression, Signaling, Courtship, and Egg Laying in the Field Cricket, <i>Gryllus assimilis</i>
Bibliographic record
Abstract
Abstract Sexual selection theory suggests males in good condition should be more successful than males in poor condition when competing with rivals for territories and mates. Understanding how condition influences the interplay between aggression, mate attraction, and courtship displays could help explain why variation is maintained in traits that confer fitness. Using laboratory‐reared Jamaican field crickets, Gryllus assimilis, we found that fine‐scale temporal components of mate attraction signals were positively correlated with body condition (residual body mass) and body size; signaling effort was positively correlated with both body condition and fine‐scale temporal signaling components; aggression was positively correlated with signaling effort; number of eggs laid was positively correlated with female body size, male body condition and aggression. Together our correlative study suggests that variation in body condition and size may drive some of the variation in cricket mate attraction signaling and aggression. Given condition and body size are influenced by foraging ability, nutrient availability and the organism’s ability to uptake and retain these essential nutrients could explain some of the persistent variation in fitness conferring traits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".