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Universal primer cocktails for fish DNA barcoding

2007· article· en· W2103330559 on OpenAlexafffund
Natalya Ivanova, Tyler Zemlak, Robert Hanner, Paul D. N. Hebert

Bibliographic record

VenueMolecular Ecology Notes · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsOntario Innovation TrustOntario Genomics InstituteGenome CanadaGordon and Betty Moore Foundation
KeywordsPrimer (cosmetics)BiologyDNA barcodingBarcodePolymerase chain reactionComputational biologyGeneticsFisheryGeneEvolutionary biologyComputer scienceChemistry

Abstract

fetched live from OpenAlex

Abstract Reliable recovery of the 5′ region of the cytochrome c oxidase 1 (COI) gene is critical for the ongoing effort to gather DNA barcodes for all fish species. In this study, we develop and test primer cocktails with a view towards increasing the efficiency of barcode recovery. Specifically, we evaluate the success of polymerase chain reaction amplification and the quality of resultant sequences using three primer cocktails on DNA extracts from representatives of 94 fish families. Our results show that M13‐tailed primer cocktails are more effective than conventional degenerate primers, allowing barcode work on taxonomically diverse samples to be carried out in a high‐throughput fashion.

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)0.007
metaresearch head score (Gemma)0.012
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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.005

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 head0.018
GPT teacher head0.281
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
GenreMethods

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

Citations1,492
Published2007
Admission routes2
Has abstractyes

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