A genetic atlas for the butterflies of continental Canada and United States
Bibliographic record
Abstract
Multi-locus genetic data for phylogeographic studies is generally limited in geographic and taxonomic scope as most studies only examine a few related species. The strong adoption of DNA barcoding has generated large datasets of mtDNA COI sequences. This work examines the butterfly fauna of Canada and United States based on 13,236 COI barcode records derived from 619 species. It compiles i) geographic maps depicting the spatial distribution of haplotypes, ii) haplotype networks (minimum spanning trees), and iii) standard indices of genetic diversity such as nucleotide diversity (π), haplotype richness (H), and a measure of spatial genetic structure (GST). High intraspecific genetic diversity and marked spatial structure were observed in the northwestern and southern North America, as well as in proximity to mountain chains. While species generally displayed concordance between genetic diversity and spatial structure, some revealed incongruence between these two metrics. Interestingly, most species falling in this category shared their barcode sequences with one at least other species. Aside from revealing large-scale phylogeographic patterns and shedding light on the processes underlying these patterns, this work also exposed cases of potential synonymy and hybridization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".