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Record W4410933321 · doi:10.1007/s13313-025-01056-z

First report of Boeremia exigua causing leaf spot of tobacco (Nicotiana tabacum) in China

2025· article· en· W4410933321 on OpenAlexaff
Tingting Xu, Pan Ma, Rubing Xu, Tom Hsiang, Junbin Huang, Lu Zheng, Yuan Fang, Yanyan Li

Bibliographic record

VenueAustralasian Plant Pathology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of Guelph
FundersHubei Tobacco Company
KeywordsNicotiana tabacumBiologyChinaLeaf spotBotanyExiguaEntomologySweet spotSpodopteraGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Tobacco ( Nicotiana tabacum L.) is an economically important crop, widely cultivated in China. Since 2021, a new leaf spot disease has been seen frequently in Enshi, Xiangyang, Yichang, and Shiyan, all in Hubei Province, China. Diseased leaves exhibiting roundish lesions with greenish-yellow edges were collected to determine the causal agent in summer 2022. After isolation, morphological characterization, and molecular identification (ITS, LSU, and TUB), the pathogen of the new tobacco leaf spot disease was identified as Boeremia exigua. Inoculation tests showed that B. exigua strains could cause this disease on detached tobacco leaves, and fungi were re-isolated with morphology identical to the inoculated strain, confirming Koch’s postulates. This is the first report of tobacco leaf spot caused by B. exigua worldwide.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.833

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 science0.0000.000
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 head0.244
Teacher spread0.235 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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