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Record W4391475002 · doi:10.1080/07060661.2024.2303650

<i>Fusarium clavum</i> causes sugar beet seedling root rot in Wyoming, USA

2024· article· en· W4391475002 on OpenAlexvenueno aff
Mohamed F. R. Khan, M. Z. R. Bhuiyan, Dilip K. Lakshman, Luis E. Del Rio Medoza, Leah Wimmer, M. E. Otto, Adnan Ismaiel, Abdolbaset Azizi

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsSugar beetRoot rotSeedlingFusariumSugarHorticultureAgronomyBiologyFood science

Abstract

fetched live from OpenAlex

Seedling rot in sugar beet was observed at Snyder Farms, Wyoming, USA, in April 2022. The diseased seedlings exhibited water-soaked brown to blackish lesions in hypocotyls with poor root systems. Four fungal isolates were retrieved from the diseased samples, and their morphological features were found to be identical to those of previously reported Fusarium species. Artificial inoculation with isolates developed similar symptoms to those observed in the field samples. Based on morphological characteristics, pathogenicity assays, sequence homologies of the internal transcribed spacer, translation elongation factor (tef1α), largest subunit of RNA polymerase II (rpb2), β-tubulin (β-tub), and multilocus phylogenic analyses with tef1α and rpb2, the causal agent was identified as Fusarium clavum (F. incarnatum-equiseti species complex 5). This is the first worldwide report of sugar beet seedling rot caused by F. clavum, detected in Wyoming, USA. This finding will help to formulate effective management practices to manage the pathogen and prevent its widespread occurrence.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.420

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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