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Record W2051623543 · doi:10.1111/1755-0998.12082

Advancing nematode barcoding: A primer cocktail for the cytochrome <i>c</i> oxidase subunit I gene from vertebrate parasitic nematodes

2013· article· en· W2051623543 on OpenAlexafffund
Sean W. J. Prosser, María G. Velarde-Aguilar, Virginia León‐Régàgnon, Paul D. N. Hebert

Bibliographic record

VenueMolecular Ecology Resources · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of Guelph
FundersConsejo Nacional de Ciencia y TecnologíaGovernment of CanadaOntario Genomics InstituteGenome CanadaNational Science Foundation
KeywordsBiologyDNA barcodingPhylumCytochrome c oxidase subunit IPrimer (cosmetics)NematodeEvolutionary biologyCytochrome c oxidasePhylogeneticsVertebrateMitochondrial DNAGeneBarcodeZoologyGeneticsEcologyMitochondrion

Abstract

fetched live from OpenAlex

Although nematodes are one of the most diverse metazoan phyla, species identification through morphology is difficult. Several genetic markers have been used for their identification, but most do not provide species-level resolution in all groups, and those that do lack primer sets effective across the phylum, precluding high-throughput processing. This study describes a cocktail of three novel primer pairs that overcome this limitation by recovering cytochrome c oxidase I (COI) barcodes from diverse nematode lineages parasitic on vertebrates, including members of three orders and eight families. Its effectiveness across a broad range of nematodes enables high-throughput processing.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.003

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 head0.008
GPT teacher head0.268
Teacher spread0.260 · 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

Citations146
Published2013
Admission routes2
Has abstractyes

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