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Record W2126507632 · doi:10.1071/is12026

Challenging species delimitation in Collembola: cryptic diversity among common springtails unveiled by DNA barcoding

2012· article· en· W2126507632 on OpenAlexfundno aff
David Porco, Anne Bedòs, Penelope Greenslade, Dariusz Skarżyński, Mark I. Stevens, Bettine Jansen van Vuuren, Louis Deharveng

Bibliographic record

VenueInvertebrate Systematics · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCollembola Taxonomy and Ecology Studies
Canadian institutionsnot available
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaOntario Genomics InstituteOffice of Polar ProgramsAustralian GovernmentGenome Canada
KeywordsBiologyDNA barcodingIntraspecific competitionSpecies complexInterspecific competitionTaxonomy (biology)TaxonEcologySystematicsEvolutionary biologyZoologyPhylogenetic tree

Abstract

fetched live from OpenAlex

Collembola is one of the major functional groups in soil as well as a model taxon in numerous disciplines. Therefore the accurate identification of specimens is critical, but could be jeopardised by cases of cryptic diversity. Several populations of six well characterised species of springtails were sequenced using the COI barcode fragment as a contribution to the global Collembola barcoding campaign. Each species showed high intraspecific divergence, comparable to interspecific sequence divergence values observed in previous studies and in 10 congeneric species barcoded here as a reference. The nuclear marker, 28S, confirmed all the intraspecific lineages found with COI, supporting the potential specific status of these entities. The implications of this finding for taxonomy and for disciplines relying on species names, such as evolution and ecology, are discussed.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.043
GPT teacher head0.206
Teacher spread0.163 · 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

Citations117
Published2012
Admission routes1
Has abstractyes

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