Phylogenomics and species delimitation in the brown snake <i>Storeria dekayi</i> (Natricidae)
Bibliographic record
Abstract
Abstract The brown snake, Storeria dekayi , is distributed across southeastern Canada, the eastern United States, and eastern Mexico, with isolated records in Central America. Despite its broad range, S. dekayi is currently recognized as a single species. Historically, eight subspecies were described based primarily on head coloration patterns, but subsequent genomic analyses of populations from the U.S.A led to their synonymization. Recently, a population discovered in the Cuatro Cienegas Basin, Coahuila, Mexico has been suggested to represent an undescribed endemic species. The aim of this study is to investigate the relationships within S. dekayi , with an emphasis on the previously unstudied populations from Mexico and Central America. To this end, we generated genomic data (ddRADseq) to conduct phylogenetic analyses, species-tree estimation, population-structure analyses, and species delimitation. Concatenated likelihood analyses estimated a tree in which populations of S. dekayi from the south-central U.S. were paraphyletic relative to an undescribed species from the Cuatro Cienegas Basin. Population structure and species delimitation analyses suggest the existence of three distinct species, including the populations from eastern North America (recognized as S. dekayi ), the population from Cuatro Cienegas, and the populations of S. dekayi from eastern Mexico and Central America. However, we conservatively recognize only two species.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".