Implications of Hybridization, NUMTs, and Overlooked Diversity for DNA Barcoding of Eurasian Ground Squirrels
Bibliographic record
Abstract
The utility of DNA Barcoding for species identification and discovery has catalyzed a concerted effort to build the global reference library; however, many animal groups of economical or conservational importance remain poorly represented. This study aims to contribute DNA barcode records for all ground squirrel species (Xerinae, Sciuridae, Rodentia) inhabiting Eurasia and to test efficiency of this approach for species discrimination. Cytochrome c oxidase subunit 1 (COI) gene sequences were obtained for 97 individuals representing 16 ground squirrel species of which 12 were correctly identified. Taxonomic allocation of some specimens within four species was complicated by geographically restricted mtDNA introgression. Exclusion of individuals with introgressed mtDNA allowed reaching a 91.6% identification success rate. Significant COI divergence (3.5-4.4%) was observed within the most widespread ground squirrel species (Spermophilus erythrogenys, S. pygmaeus, S. suslicus, Urocitellus undulatus), suggesting the presence of cryptic species. A single putative NUMT (nuclear mitochondrial pseudogene) sequence was recovered during molecular analysis; mitochondrial COI from this sample was amplified following re-extraction of DNA. Our data show high discrimination ability of 100 bp COI fragments for Eurasian ground squirrels (84.3%) with no incorrect assessments, underscoring the potential utility of the existing reference librariy for the development of diagnostic 'mini-barcodes'.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".