Calling, Courtship, and Condition in the Fall Field Cricket, Gryllus pennsylvanicus
Bibliographic record
Abstract
Theoretically, sexual signals should provide honest information about mating benefits and many sexually reproducing species use honest signals when signalling to potential mates. Male crickets produce two types of acoustic mating signals: a long-distance mate attraction call and a short-range courtship call. We tested whether wild-caught fall field cricket (Gryllus pennsylvanicus) males in high condition (high residual mass or large body size) produce higher effort calls (in support of the honest signalling hypothesis). We also tested an alternative hypothesis, whether low condition males produce higher effort calls (in support of the terminal investment hypothesis). Several components of long-distance mate attraction calls honestly reflected male body size, with larger males producing louder mate attraction calls at lower carrier frequencies. Long-distance mate attraction chirp rate dishonestly signalled body size, with small males producing faster chirp rates. Short-range courtship calls dishonestly reflected male residual mass, as chirp rate and pulse rate were best explained by a curvilinear function of residual mass. By producing long-distance mate attraction calls and courtship calls with similar or higher effort compared to high condition males, low condition males (low residual mass or small body size) may increase their effort in current reproductive success at the expense of their future reproductive success, suggesting that not all sexual signals are honest.
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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 | 0.001 | 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) | 0.001 | 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".