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Record W4316014968 · doi:10.1139/cjm-2022-0165

Detection of the pathogenic fungus <i>Cordyceps farinosa</i> in the <i>Thitarodes armoricanus</i> soil-rearing environment based on nucleic acid targets

2023· article· en· W4316014968 on OpenAlexvenueno aff
Chaoqun Tong, Tian Li, Shisui Luo, Ruoni Chen, Shijiang Chen, Junhong Wei, Yuling Qing, Shaorong Qin, Guoqing Pan, Chunfeng Li, Zeyang Zhou

Bibliographic record

VenueCanadian Journal of Microbiology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPrimer (cosmetics)FungusGenomeBotanyHorticultureGeneticsGene

Abstract

fetched live from OpenAlex

Cordyceps farinosa, an entomopathogenic fungus, infects and leads to high mortality of Thitarodes armoricanus larvae, which die soon after the infection of C. farinose, usually before the colonization of Ophiocordyceps sinensis owing to competitive inhibition and fruiting body formation. Therefore, monitoring C. farinosa in the O. sinensis cultivation environment is critical for minimizing the C. farinosa infection-induced losses. In this study, we initially designed a PCR primer pair (Tar-1F/Tar-1R) through open reading frame prediction and homology comparison of the C. farinosa genome sequence. This primer pair can detect both C. farinosa and Samsoniella hepiali. To further distinguish, primers (ITS5-172/ITS4-95) were then designed to selectively amplify the large ribosomal subunit sequences in the C. farinosa genome. All these primers were applied in combination for detection of C. farinosa in soil samples. The sensitivity reached a detection limit of 1 × 10 6 spores/g soil. In addition, these primers can detect the presence of C. farinosa in dead T. armoricanus larval samples. This newly established rapid detection method provides important information for C. farinosa control during O. sinensis cultivation.

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)0.001
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 score0.399
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.164
Teacher spread0.157 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of MicrobiologySame topicEntomopathogenic Microorganisms in Pest ControlFrench-language works237,207