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Record W1983213449 · doi:10.1139/g06-025

Benchmarking DNA barcodes: an assessment using available primate sequences

2006· article· en· W1983213449 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueGenome · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsConcordia UniversityUniversity of Guelph
Fundersnot available
KeywordsDNA barcodingBiologyEvolutionary biologyPhylogenetic treeBiodiversityDNA sequencingPhylogeneticsDNAComputational biologyEnvironmental DNAGeneticsEcologyGene

Abstract

fetched live from OpenAlex

DNA barcoding has been recently promoted as a method for both assigning specimens to known species and for discovering new and cryptic species. Here we test both the potential and the limitations of DNA barcodes by analysing a group of well-studied organisms--the primates. Our results show that DNA barcodes provide enough information to efficiently identify and delineate primate species, but that they cannot reliably uncover many of the deeper phylogenetic relationships. Our conclusion is that these short DNA sequences do not contain enough information to build reliable molecular phylogenies or define new species, but that they can provide efficient sequence tags for assigning unknown specimens to known species. As such, DNA barcoding provides enormous potential for use in global biodiversity 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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.431

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 head0.033
GPT teacher head0.325
Teacher spread0.292 · 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