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Record W3133908527 · doi:10.1038/s42003-021-01834-7

High resolution DNA barcode library for European butterflies reveals continental patterns of mitochondrial genetic diversity

2021· article· en· W3133908527 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications Biology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsUniversity of Guelph
FundersAgencia Estatal de InvestigaciónProvincia autonoma di Bolzano - Alto AdigeGeneralitat de CatalunyaMinisterio de Economía y CompetitividadAcademy of Finland
KeywordsMitochondrial DNABarcodeDNA barcodingGenetic diversityDiversity (politics)BiologyEvolutionary biologyGeographyGeneticsSociologyComputer scienceGeneAnthropology

Abstract

fetched live from OpenAlex

The study of global biodiversity will greatly benefit from access to comprehensive DNA barcode libraries at continental scale, but such datasets are still very rare. Here, we assemble the first high-resolution reference library for European butterflies that provides 97% taxon coverage (459 species) and 22,306 COI sequences. We estimate that we captured 62% of the total haplotype diversity and show that most species possess a few very common haplotypes and many rare ones. Specimens in the dataset have an average 95.3% probability of being correctly identified. Mitochondrial diversity displayed elevated haplotype richness in southern European refugia, establishing the generality of this key biogeographic pattern for an entire taxonomic group. Fifteen percent of the species are involved in barcode sharing, but two thirds of these cases may reflect the need for further taxonomic research. This dataset provides a unique resource for conservation and for studying evolutionary processes, cryptic species, phylogeography, and ecology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.246
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it