Cryptic diversity in the New World burying beetle fauna: Nicrophorus hebes Kirby- new status as a resurrected name (Coleoptera: Silphidae: Nicrophorinae)
Bibliographic record
Abstract
Burying beetles (Silphidae: Nicrophorus Fabricius, 1775) are known for their biparental care and monopolization of small vertebrate carcasses in subterranean crypts. They have been the focus of intense behavioral ecological research since the 1980s and the New World fauna was taxonomically revised in the 1980s. Here, with new molecular, ecological, reproductive incompatability, and morphological data, we report the discovery that N. vespilloides in most of North America, except Alaska + Yukon + Northwest Territories, is not conspecific with Old World N. vespilloides. DNA barcode data split this species into two BINs, each shows different habitat preferences, most larvae from hybrid crosses fail to reach four days of age, and diagnostic characters were found on the epipleuron and metepisternum that help to separate the species. The oldest available name for this other set of North American populations is Nicrophorus hebes Kirby, 1837, which we now treat as valid (new status). This study brings the New World total to 22 species for the genus, and given the rarity of N. hebes, and its tight association with wetlands, justifies further investigation into its conservation status.
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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".