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Record W2260738652 · doi:10.1534/g3.115.020057

Genome Sequences of Three Phytopathogenic Species of the Magnaporthaceae Family of Fungi

2015· article· en· W2260738652 on OpenAlexaff
Laura H. Okagaki, Cristiano Caixeta Nunes, Joshua Sailsbery, Brent Clay, Doug Brown, T. Buchanan John, Yeonyee Oh, Nelson D. Young, Michael G. FitzGerald, Brian J. Haas, Qiandong Zeng, Sarah Young, Xian Adiconis, Joshua Z. Levin, Thomas K. Mitchell, Patricia A. Okubara, Mark Farman, Linda M. Kohn, Bruce W. Birren, Li‐Jun Ma, Ralph A. Dean

Bibliographic record

VenueG3 Genes Genomes Genetics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious Diseases
KeywordsBiologyGenomeGeneDNA sequencingWhole genome sequencingTake-allGeneticsBotanyFungus

Abstract

fetched live from OpenAlex

Magnaporthaceae is a family of ascomycetes that includes three fungi of great economic importance: Magnaporthe oryzae, Gaeumannomyces graminis var. tritici, and Magnaporthe poae. These three fungi cause widespread disease and loss in cereal and grass crops, including rice blast disease (M. oryzae), take-all disease in wheat and other grasses (G. graminis), and summer patch disease in turf grasses (M. poae). Here, we present the finished genome sequence for M. oryzae and draft sequences for M. poae and G. graminis var. tritici. We used multiple technologies to sequence and annotate the genomes of M. oryzae, M. poae, and G. graminis var. tritici. The M. oryzae genome is now finished to seven chromosomes whereas M. poae and G. graminis var. tritici are sequenced to 40.0× and 25.0× coverage respectively. Gene models were developed by the use of multiple computational techniques and further supported by RNAseq data. In addition, we performed preliminary analysis of genome architecture and repetitive element DNA.

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 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 score0.351
Threshold uncertainty score0.738

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 science0.0010.000
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 head0.030
GPT teacher head0.225
Teacher spread0.195 · 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.

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

Citations42
Published2015
Admission routes1
Has abstractyes

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