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Record W3200865738 · doi:10.1080/07060661.2021.1982012

First report of the southern corn rust pathogen <i>Puccinia polysora</i> on <i>Zea mays</i> in North Dakota

2021· article· en· W3200865738 on OpenAlexvenueno aff
Jessica Halvorson, Yong‐Jae Kim, Upinder Gill, Andrew Friskop

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsRust (programming language)Zea maysBiologyPucciniaAgronomyField cornSporePathogenBotanyMicrobiology

Abstract

fetched live from OpenAlex

Southern corn rust, caused by Puccinia polysora, is a yield-limiting disease on corn (Zea mays). As a biotrophic fungal pathogen, P. polysora requires a living host for its survival. Southern corn rust is favoured by high-temperatures and humid environmental conditions, and therefore is more prevalent in the southern United States. In August 2020, corn plants displaying signs and symptoms of southern rust were collected in a field in Grand Forks County, North Dakota. Due to its rare occurrence in the region, spores of the pathogen were isolated and analyzed morphologically, and found to be consistent with P. polysora. This identification was confirmed by PCR analysis and Sanger sequencing, and demonstrated further using Koch’s postulates. The discovery of P. polysora poses a potential threat to corn yields across North Dakota, and surveillance must be enhanced to predict possible epidemics in the future.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.177
Teacher spread0.163 · 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 designCase report
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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Plant PathologySame topicWheat and Barley Genetics and PathologyFrench-language works237,207