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Record W2135777664 · doi:10.1080/07060661.2014.920921

Identification of <i>Pythium</i> spp. from the rhizosphere of soybeans in Ontario, Canada

2014· article· en· W2135777664 on OpenAlexaffvenueabout
Geneviève Marchand, Yuanhong Chen, Nahom Ahferom Berhane, Lai Wei, C. André Lévesque, Allen Xue

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPythium ultimumPythiumDamping offBiologyRoot rotRhizosphereInternal transcribed spacerRibosomal DNABotanySeedlingHorticultureAgronomyRibosomal RNARhizoctonia solaniPhylogeneticsBacteriaGene

Abstract

fetched live from OpenAlex

Production of soybean in short-season areas of Canada is affected by Pythium species causing seed rot, seedling damping-off and root rot under the cool, moist conditions prevalent early in the growing season. To determine which Pythium species infect soybean plants under these conditions, soil samples were collected in 2010, 2011 and 2012 from soybean fields in Ontario where symptoms of damping-off or root rot were observed. Pythium spp. were isolated from soil using a seed baiting approach and selective media. PCR amplification and sequencing of the internal transcribed spacer of the nuclear ribosomal DNA allowed for identification of six different Pythium species (out of a total of 104 strains). Pythium ultimum var. ultimum (56.7%) and P. sylvaticum (29.8%) were the most frequently isolated species over all sampling years. Other species isolated included P. dissotocum (6.7%), P. ultimum var. sporangiiferum (3.8%), P. irregulare (1.9%), and P. hypogynum (1.0%).

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 score0.664
Threshold uncertainty score0.201

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 head0.008
GPT teacher head0.153
Teacher spread0.145 · 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

Citations23
Published2014
Admission routes3
Has abstractyes

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