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Record W4403097185 · doi:10.1094/phytofr-07-24-0080-a

A High-Quality Genome Resource for the Oak Wilt Pathogen <i>Bretziella fagacearum</i>

2024· article· en· W4403097185 on OpenAlexaboutno aff
Karandeep Chahal, Mohit Mahey, C. Medina-Mora, Steven Ahrendt, Robert Riley, Anna Lipzen, Juying Yan, Emily Savage, Maxim Koriabine, Vivian Ng, Igor V. Grigoriev, T. C. Harrington, Eric L. Patterson, Timothy D. Miles, Monique L. Sakalidis

Bibliographic record

VenuePhytoFrontiers™ · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPathogenBiologyResource (disambiguation)Wilt diseaseGenomeQuality (philosophy)BotanyGeneticsComputer scienceGenePhysics

Abstract

fetched live from OpenAlex

Bretziella fagacearum is a destructive vascular wilt fungal pathogen affecting oaks in the United States and Canada. The epidemiology of oak wilt varies across different geographical locations, indicating the need to investigate the population dynamics of B. fagacearum to discern potential differences in its genotypes using genomic tools. A good-quality genome of B. fagacearum is crucial as a reference for population genetics studies. Here, we report a high-quality genome of B. fagacearum isolate C519. The genome assembly consists of nine scaffolds, corresponding to the nine chromosomes, totaling 27,072,536 bp with a GC content of 47.29%. It is predicted to encode 7,554 proteins, which are annotated using RNA sequencing data from the same isolate. The circular mitochondrial genome consists of a chromosome of 174,403 bp with a GC content of 28.59% and contains 54 open reading frames, including 14 core genes, 28 tRNAs, 4 rRNAs, and 8 hypothetical proteins. The reference genome can enhance the understanding of molecular epidemiology and biology of B. fagacearum, aiding in identifying genetic variations and pathogen–host interactions and developing diagnostic tools and disease management strategies. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2025.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.006
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.014

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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
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

Citations2
Published2024
Admission routes1
Has abstractyes

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