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Record W4410477696 · doi:10.1101/2025.05.16.654383

Incidence and attributes of chimeric COI and 18S sequences derived from nematode-infected arthropods

2025· preprint· en· W4410477696 on OpenAlexfundno aff
Jacopo D’Ercole, Robin Floyd, Sean W. J. Prosser, Saeideh Jafarpour, Paul D. N. Hebert

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsnot available
FundersCanada Foundation for InnovationGovernment of CanadaMinistry of Colleges and UniversitiesOntario GenomicsGenome Canada
KeywordsNematodeBiologyZoologyEvolutionary biologyIncidence (geometry)EcologyMathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract High-throughput sequencing is speeding the discovery of new species and making it possible to quantify the species richness of bulk samples. However, chimeric sequences can lead to both type I errors (true species mistakenly rejected) and type II errors (chimeras incorrectly viewed as valid species). This study employed nanopore sequencing to examine the incidence and nature of chimeric sequences recovered from 531 arthropod specimens infected with nematodes. Specifically, it examined chimera formation in two gene regions: the 658 bp segment of mitochondrial COI employed as the barcode region for the animal kingdom, and a 900 bp segment of nuclear 18S often employed to discriminate lineages of nematodes. This work revealed chimeras for both gene regions despite the deep sequence divergences between members of these two phyla. However, the incidence of chimeric molecules was higher for 18S than COI, with chimera formation correlating with local variation in DNA stability and conserved regions between parent sequences. Aside from demonstrating that chimeras can arise from distantly related organisms, this study provides insights into the mechanisms underlying their formation.

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 categoriesMeta-epidemiology (narrow)
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 score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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