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Record W2031169672 · doi:10.11646/zootaxa.3919.3.8

DNA barcoding and regional diversity of understudied Micropeplinae (Coleoptera: Staphylinidae) in Southwest China: phylogenetic implications <br />and a new Micropeplus from Mount Emei

2015· article· en· W2031169672 on OpenAlexaff
Vasily V. Grebennikov, Aleš Smetana

Bibliographic record

VenueZootaxa · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsAgriculture and Agri-Food CanadaCanadian Food Inspection Agency
Fundersnot available
KeywordsBiologySensuSensu strictoAllopatric speciationDNA barcodingGenusFaunaEcologyPlant litterSpecies diversityZoologyPhylogenetic treeEcosystemPopulation

Abstract

fetched live from OpenAlex

Extensive litter sampling at eight forested localities in Yunnan and Sichuan detected 381 specimens of Micropeplinae rove beetles. DNA barcoding data from 85 representative specimens were analysed to delimit species and infer their relationships. Statistical methods were implemented to assess regional species diversity of understudied Micropeplinae. The total number of sampled Micropeplinae species varied between 14 and 17, depending on a splitting versus lumping approach for allopatric populations. A single Micropeplinae species was sampled in six of eight studied localities, three species were found on Mount Gongga, while ten species were discovered on hyperdiverse Mount Emei in Sichuan. All Micropeplinae specimens from our samples belong either to the genus Cerapeplus, or to three other inclusive groups temporarily retained inside Micropeplus sensu lato. Each of the three groups potentially represents a separate genus: tesserula group, sculptus group and Micropeplus sensu stricto. A new species Micropeplus jason sp. n. from Mount Emei in Sichuan is described. Numerous illustrations introduce regional fauna and clarify the discussed morphological characters.

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)0.000
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.057
GPT teacher head0.230
Teacher spread0.173 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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