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Record W2071510336 · doi:10.1073/pnas.0905845106

A DNA barcode for land plants

2009· article· en· W2071510336 on OpenAlexafffund
Peter M. Hollingsworth, Laura L. Forrest, John L. Spouge, Mehrdad Hajibabaei, Sujeevan Ratnasingham, Michelle van der Bank, Mark W. Chase, Robyn S. Cowan, David L. Erickson, Aron J. Fazekas, Sean W. Graham, Karen E. James, Ki-Joong Kim, W. John Kress, Harald Schneider, Jonathan Van Alphen-Stahl, Spencer C. H. Barrett, Cássio van den Berg, Diego Bogarín, Kevin S. Burgess, Kenneth M. Cameron, Mark A. Carine, Juliana Chacón, Alexandra Clark, James J. Clarkson, Ferozah Conrad, Dion S. Devey, C. S. Ford, Terry A. Hedderson, Michelle L. Hollingsworth, Brian C. Husband, Laura J. Kelly, Prasad Kesanakurti, Jung Sung Kim, Young‐Dong Kim, Renaud Lahaye, Hae-Lim Lee, David G. Long, Santiago Madriñán, Olivier Maurin, Isabelle Meusnier, Steven G. Newmaster, Chong-Wook Park, Diana M. Percy, Gitte Petersen, James Richardson, Gerardo A. Salazar, Vincent Savolainen, Ole Seberg, M. J. Wilkinson, Dong‐Keun Yi, Damon P. Little

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaUniversity of Guelph
FundersNational Institutes of HealthU.S. National Library of MedicineAlfred P. Sloan FoundationNational Research FoundationGenome CanadaGordon and Betty Moore Foundation
KeywordsBarcodeDNA barcodingrpoBBiologyGeneLocus (genetics)DNA sequencingGeneticsComputational biologyDNAPolymerase chain reactionEvolutionary biologyComputer science16S ribosomal RNA

Abstract

fetched live from OpenAlex

DNA barcoding involves sequencing a standard region of DNA as a tool for species identification. However, there has been no agreement on which region(s) should be used for barcoding land plants. To provide a community recommendation on a standard plant barcode, we have compared the performance of 7 leading candidate plastid DNA regions (atpF-atpH spacer, matK gene, rbcL gene, rpoB gene, rpoC1 gene, psbK-psbI spacer, and trnH-psbA spacer). Based on assessments of recoverability, sequence quality, and levels of species discrimination, we recommend the 2-locus combination of rbcL+matK as the plant barcode. This core 2-locus barcode will provide a universal framework for the routine use of DNA sequence data to identify specimens and contribute toward the discovery of overlooked species of land plants.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.015

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 head0.033
GPT teacher head0.296
Teacher spread0.263 · 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 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

Citations2,802
Published2009
Admission routes2
Has abstractyes

Explore more

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