Sexual Dimorphism in North American Coccinellids: Sexing Methods for Species of Coccinella L. (Coleoptera: Coccinellidae) and Implications for Conservation Research
Bibliographic record
Abstract
Coccinellids typically do not show exaggerated sexual dimorphisms, and the only reliable sexing methods for some species have been dissection and behavioral observations. Behavioral methods can potentially lead to sex identification but are very time consuming, require exposing sexually naïve individuals to conspecifics, and risk incorrect identification since homosexual mounting in these species has been observed in the laboratory. Research involving use of live specimens requires techniques to non-invasively determine the sex of individuals, but such methods have not been clearly or fully described in the literature. Closer examination of the species Coccinella novemnotata Herbst, Coccinella septempunctata L., Coccinella transversoguttata richardsoni Brown, and Coccinella trifasciata perplexa Mulsant has led to the discovery of a reliable and efficient way to differentiate the sexes by looking at the shape of the seventh sternite (fifth visible), and this method has been demonstrated to be 100% reliable for all four species. Another, even more rapid, method uses the shape of a prominent black pronotal marking and shows promise for C. novemnotata but is not applicable to the other species. Additionally, most species of Coccinella L. have males with conspicuous pale anterior coxal spots and femoral stripes that can be easily viewed, especially on mobile specimens. Morphometric data that quantify external dimorphisms and provide evidence for the reliability of using them for sexing are reported. All known external characters that can be used for sexing North American Coccinella species are consolidated for easy reference. The significance of these findings for research into the decline of native Coccinella species in the United States is discussed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".