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Record W2601087906 · doi:10.1139/gen-2016-0198

Ten years of barcoding at the African Centre for DNA Barcoding

2017· review· en· W2601087906 on OpenAlexaffvenue
B.S. Bezeng, T. Jonathan Davies, Barnabas H. Daru, R.M. Kabongo, Olivier Maurin, Kowiyou Yessoufou, Herman van der Bank, Michelle van der Bank

Bibliographic record

VenueGenome · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsDNA barcodingBiologyBarcodeEvolutionary biologyPhylogenetic treeMitochondrial DNABiodiversityGeneEcologyGenetics

Abstract

fetched live from OpenAlex

The African Centre for DNA Barcoding (ACDB) was established in 2005 as part of a global initiative to accurately and rapidly survey biodiversity using short DNA sequences. The mitochondrial cytochrome c oxidase 1 gene (CO1) was rapidly adopted as the de facto barcode for animals. Following the evaluation of several candidate loci for plants, the Plant Working Group of the Consortium for the Barcoding of Life in 2009 recommended that two plastid genes, rbcLa and matK, be adopted as core DNA barcodes for terrestrial plants. To date, numerous studies continue to test the discriminatory power of these markers across various plant lineages. Over the past decade, we at the ACDB have used these core DNA barcodes to generate a barcode library for southern Africa. To date, the ACDB has contributed more than 21 000 plant barcodes and over 3000 CO1 barcodes for animals to the Barcode of Life Database (BOLD). Building upon this effort, we at the ACDB have addressed questions related to community assembly, biogeography, phylogenetic diversification, and invasion biology. Collectively, our work demonstrates the diverse applications of DNA barcoding in ecology, systematics, evolutionary biology, and conservation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.056
GPT teacher head0.302
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2017
Admission routes2
Has abstractyes

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