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Record W3094388519 · doi:10.3897/dez.67.56163

A DNA barcode library for ground beetles of Germany: the genus Agonum Bonelli, 1810 (Insecta, Coleoptera, Carabidae)

2020· article· en· W3094388519 on OpenAlexfundno aff
Michael J. Raupach, Karsten Hannig, Jérôme Morinière, Lars Hendrich

Bibliographic record

VenueDeutsche Entomologische Zeitschrift · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsnot available
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaBundesministerium für Wissenschaft und ForschungGovernment of CanadaGenome CanadaOntario GenomicsBundesministerium für Bildung und ForschungOntario Genomics Institute
KeywordsBarcodeDNA barcodingBiologyGenusBiodiversityIntraspecific competitionZoologyEcologyComputer science

Abstract

fetched live from OpenAlex

The ground beetle genus Agonum Bonelli, 1810 is a large genus of the tribe Platynini with many species that show high amounts of intraspecific variations, making a correct identification challenging. As part of the German Barcode of Life initiative, this publication provides a comprehensive DNA barcode library for species of Agonum that are reported for Germany. In total, DNA barcodes from 258 beetles and 23 species were analysed using the Barcode of Life Data System (BOLD) workbench, including sequences from former studies and 68 newly-generated sequences. The neighbour-joining analyses, based on K2P distances, revealed distinct clustering for all studied species, with unique Barcode Index Numbers (BINs) for 15 species (65%). BIN sharing but distinct clustering was found for three species pairs: Agonum micans / Agonum scitulum , Agonum impressum / Agonum sexpunctatum and Agonum duftschmidi / Agonum emarginatum . The given dataset and its analysis represent another important step in generating a comprehensive DNA barcode library for the ground beetles of Germany and Central Europe in terms of modern biodiversity research.

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.

How this classification was reachedexpand

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 score0.749
Threshold uncertainty score0.532

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 science0.0010.000
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 head0.031
GPT teacher head0.223
Teacher spread0.192 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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Same venueDeutsche Entomologische ZeitschriftSame topicColeoptera Taxonomy and DistributionFrench-language works237,207