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Record W2967453165 · doi:10.1139/cjb-2019-0018

DNA barcoding of a complex genus, <i>Aesculus</i> L. (Sapindaceae) reveals lack of species-level resolution

2019· article· en· W2967453165 on OpenAlexvenueno aff
Deniz Aygören Uluer, Rahma Alshamrani

Bibliographic record

VenueBotany · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Species Descriptions
Canadian institutionsnot available
FundersUniversity of Reading
KeywordsBiologyDNA barcodingBotanyPhylogeneticsPhylogenetic treeGenusMonophylyCladeEvolutionary biologyGeneticsGene

Abstract

fetched live from OpenAlex

Aesculus L. is a small genus of horticulturally important trees and shrubs, comprising 13–19 species. Frequent hybridization among species, particularly in cultivation, has contributed to taxonomic confusion and difficulties in the identification of plants. In this study, we evaluated three widely employed plant DNA barcode loci, matK, and the entire ITS region (ITS1+5.8S+ITS2) as well as subunit ITS2 for 50 individuals representing 13 species of Aesculus, excluding only A. wangii (=A. assamica). In contrast to the plastid matK region, both the ITS and ITS2 loci displayed low levels of species discrimination, especially in our “first hit” BLASTn searches. We also presented the phylogeny of Aesculus based on matK and the entire ITS region, with additional matK and ITS sequences from GenBank. Our results show that Aesculus chinensis, A. flava, A. glabra, A. pavia, and A. sylvatica are probably not monophyletic. Furthermore, with the widest taxon coverage until now, the current study highlights the importance of sampling multiple individuals, not only for DNA barcoding, but also for phylogenetic studies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.459

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 science0.0000.000
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 head0.065
GPT teacher head0.265
Teacher spread0.200 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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