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Record W2342549110 · doi:10.1371/journal.pone.0154363

Assessing DNA Barcodes for Species Identification in North American Reptiles and Amphibians in Natural History Collections

2016· article· en· W2342549110 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la RechercheOntario Genomics InstituteGovernment of CanadaNational Museum of Natural HistoryGenome CanadaOntario GenomicsHarvard UniversityMuseum of Vertebrate ZoologySmithsonian Institution
KeywordsDNA barcodingBiologyBarcodeBiodiversitySpecies complexAmphibianSpecies identificationZoologyEcologyEvolutionary biologyPhylogenetic tree

Abstract

fetched live from OpenAlex

BACKGROUND: High rates of species discovery and loss have led to the urgent need for more rapid assessment of species diversity in the herpetofauna. DNA barcoding allows for the preliminary identification of species based on sequence divergence. Prior DNA barcoding work on reptiles and amphibians has revealed higher biodiversity counts than previously estimated due to cases of cryptic and undiscovered species. Past studies have provided DNA barcodes for just 14% of the North American herpetofauna, revealing the need for expanded coverage. METHODOLOGY/PRINCIPAL FINDINGS: This study extends the DNA barcode reference library for North American herpetofauna, assesses the utility of this approach in aiding species delimitation, and examines the correspondence between current species boundaries and sequence clusters designated by the BIN system. Sequences were obtained from 730 specimens, representing 274 species (43%) from the North American herpetofauna. Mean intraspecific divergences were 1% and 3%, while average congeneric sequence divergences were 16% and 14% in amphibians and reptiles, respectively. BIN assignments corresponded with current species boundaries in 79% of amphibians, 100% of turtles, and 60% of squamates. Deep divergences (>2%) were noted in 35% of squamate and 16% of amphibian species, and low divergences (<2%) occurred in 12% of reptiles and 23% of amphibians, patterns reflected in BIN assignments. Sequence recovery declined with specimen age, and variation in recovery success was noted among collections. Within collections, barcodes effectively flagged seven mislabeled tissues, and barcode fragments were recovered from five formalin-fixed specimens. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that DNA barcodes can effectively flag errors in museum collections, while BIN splits and merges reveal taxa belonging to deeply diverged or hybridizing lineages. This study is the first effort to compile a reference library of DNA barcodes for herpetofauna on a continental scale.

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.

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 score0.537
Threshold uncertainty score0.294

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 head0.056
GPT teacher head0.264
Teacher spread0.208 · 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