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Record W2789692501 · doi:10.1111/efp.12418

q<scp>PCR</scp> quantification of <i>Ophiognomonia clavigignenti‐juglandacearum</i> from infected butternut trees under different release treatments

2018· article· en· W2789692501 on OpenAlexafffund
Philippe Tanguay, Martine Blais, Amélie Potvin, Don Stewart, Donald M. Walker, Nicolas Nadeau-Thibodeau, Pierre DesRochers, Danny Rioux

Bibliographic record

VenueForest Pathology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Interactions Research
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersMinistère de la Défense NationaleCanadian Armed ForcesUniversité Laval
KeywordsConidiumBiologyTaqManCankerSporePathogenPolymerase chain reactionReal-time polymerase chain reactionBotanyHorticultureVeterinary medicineMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

Summary The use of a molecular assay for quantifying conidia of Ophiognomonia clavigignenti‐juglandacearum , the fungal pathogen responsible of butternut canker, was investigated. Purified DNA from conidia collected on glass fibre filters of a passive rain collectors was quantified using a TaqMan real‐time quantitative polymerase chain reaction (q PCR ) assay. The q PCR assay could specifically discriminate the target species from all other North American known species of Ophiognomonia , and it was sensitive enough to repeatedly detect one conidium. A linear relationship between numbers of conidia and q PCR C t values was determined, and used to assess the sporulation of the pathogen under trees that were released to promote their vigour. In total, 977 samples of field‐captured conidia from 49 trees, at two locations, and from two successive growing seasons were analysed. No significant difference of sporulation was observed under control and release treatments. However, our results demonstrated that q PCR assay was reliable for detecting and quantifying O. clavigignenti‐juglandacearum from environmental samples, which will be useful to assess further control methods for this disease.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.633

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 head0.019
GPT teacher head0.288
Teacher spread0.268 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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