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Record W3040309181 · doi:10.3897/zookeys.894.37862

DNA barcodes reveal 63 overlooked species of Canadian beetles (Insecta, Coleoptera)

2019· article· en· W3040309181 on OpenAlexafffundabout
Mikko Pentinsaari, Robert S. Anderson, Lech Borowiec, Patrice Bouchard, Adam Brunke, Hume Douglas, Andrew B. T. Smith, Paul D. N. Hebert

Bibliographic record

VenueZooKeys · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsAgriculture and Agri-Food CanadaCanadian Museum of NatureUniversity of Guelph
FundersGenome Canada
KeywordsNearctic ecozoneDNA barcodingBiologySynonym (taxonomy)ZoologyHydrophilidaeTaxonomy (biology)GenusConfusionEcologyTaxon

Abstract

fetched live from OpenAlex

This study demonstrates the power of DNA barcoding to detect overlooked and newly arrived taxa. Sixty-three species of Coleoptera representing 25 families are studied based on DNA barcode data and morphological analysis of the barcoded specimens. Three of the species involve synonymies or previous taxonomic confusion in North America, while the first Canadian records are published for 60 species. Forty-two species are adventive in North America, and 40 of these adventive species originate from the Palaearctic region. Three genera are recorded from the Nearctic region for the first time:CoelostomaBrullé, 1835 (Hydrophilidae),ScydmoraphesReitter, 1891 (Staphylinidae), andLythrariaBedel, 1897 (Chrysomelidae). Two new synonymies are established:Mycetoporus triangulatusCampbell, 1991 (Staphylinidae) is a junior synonym ofMycetoporus reicheiPandellé, 1869,syn. nov.whileBledius philadelphicusFall, 1919 (Staphylinidae) is a junior synonym ofBledius gallicus(Gravenhorst, 1806),syn. nov.The previously suggested move ofCtenicera tigrina(Fall, 1901) to the genusPseudanostirusDolin, 1964 (Elateridae) is formalized, resulting inPseudanostirus tigrinus(Fall, 1901),comb. nov.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.710

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.183
Teacher spread0.166 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations51
Published2019
Admission routes3
Has abstractyes

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