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Record W3202034507 · doi:10.1080/07060661.2021.1986744

Powdery mildews on crops and ornamentals in Canada: a summary of the phylogeny and taxonomy from 2000 – 2019

2021· article· en· W3202034507 on OpenAlexaffvenueabout
Miao Liu, Uwe Braun

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPowdery Mildew Fungal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPowdery mildewOrnamental plantBiologyTaxonomy (biology)Phylogenetic treeMildewPlant diseaseBotanyBiotechnology

Abstract

fetched live from OpenAlex

Powdery mildew diseases on crops and ornamental plants are common and cause significant economic losses, by reducing the yield and quality of crops and downgrading the value of ornamentals. In surveys published annually in the Canadian Plant Disease Survey, powdery mildews were reported frequently. In recent years, the taxonomy of powdery mildew fungi has changed tremendously as the result of the increased application of molecular phylogenetic analyses. Several generic concepts have been re-adjusted. Many traditionally considered species turned out to be a complex of several phylogenetic species. In order to facilitate effective communication in the scientific community, it is important to apply the current correct names for field identifications. In this document, we summarize the powdery mildew fungi reported in the Canadian Plant Disease Survey from 2000 to 2019, address the taxonomic and nomenclatural issues associated with the listed species, and tentatively suggest correct names based on host plants wherever possible. Nevertheless, a reliable identification of the powdery mildew must depend on DNA sequence analyses and morphological examinations.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0130.016
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.158
Teacher spread0.144 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2021
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Plant PathologySame topicPowdery Mildew Fungal DiseasesFrench-language works237,207