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Record W2903190517 · doi:10.1111/jph.12765

<i>Colletotrichum</i> species associated with cassava anthracnose in China

2018· article· en· W2903190517 on OpenAlexfundno aff
Xianbao Liu, Tao Shi, Boxun Li, Jimiao Cai, Chaoping Li, Huang Guixiu

Bibliographic record

VenueJournal of Phytopathology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersMinistry of Agriculture - Saskatchewan
KeywordsBiologyColletotrichumPhylogenetic treeBotanyVirulenceChinaPhylogenetic relationshipGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Anthracnose caused by Colletotrichum (CAD) is an economically important disease of cassava; however, research on its species diversity and geographical distribution of Colletotrichum in China remains limited. In this study, we investigated the phylogenetic diversity of Colletotrichum isolates associated with symptomatic leaf tissues of cassava from Guangxi and Yunnan provinces in China and aimed to confirm their identification using advanced techniques. Based on multi‐locus phylogenetic analyses and phenotypic characteristics, we identified four species from the isolates, comprising C. plurivorum, C. karstii, C. fructicola and C. siamense, and we found variation in degrees of virulence among the species and between cassava varieties. Our results are the first to report these species from cassava, and they provide a basis for the development of management strategies for CAD in cassava.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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 designObservational
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

Citations25
Published2018
Admission routes1
Has abstractyes

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