Sexual dimorphism in the badlands cricket (Orthoptera, Gryllinae, Gryllus personatus)
Bibliographic record
Abstract
Sexual dimorphism (SD) is a common phenomenon in sexual species and can manifest in a variety of ways. Sexual size dimorphism (SSD) is commonly investigated, but it can be confounded with sexual shape dimorphism (SShD) if multivariate measures of size are not used. Univariate studies may also overestimate the prevalence or direction of SSD when the sexes are strikingly different in shape, which may be an issue in taxa such as Orthoptera and other terrestrial arthropods where maximum body size is strongly constrained. Here we tested for the occurrence of both SSD and SShD in the badlands cricket Gryllus personatus (Orthoptera, Gryllinae). We measured four body size dimensions—maxillae span, head width, pronotum length, and mean hind femur length—and used multivariate methods to test whether male and female adult badlands crickets were sexually dimorphic in size and/or shape. All the univariate dimensions were sexually dimorphic, with males having wider heads and maxillae than females and females having longer pronota and hind femora than males, which indicates SShD. However, multivariate methods failed to detect SSD, instead confirming that the sexes primarily differ in body shape. We show how a simple ratio of head width to pronotum length captures SShD in badlands crickets and apply it to iNaturalist, a citizen science platform, to broaden our findings. We propose that orthopterists studying SD minimally measure head width, pronotum length, and hind femur length as a standard that will allow a more repeatable and generalizable assessment of the prevalence and direction of both SSD and SShD.
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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".