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Record W3036063807 · doi:10.1094/php-01-20-0003-rs

ClubrootTracker: A Resource to Plan a Clubroot-Free Farm

2020· article· en· W3036063807 on OpenAlexafffund
Kevin Muirhead, Christopher D. Todd, Yangdou Wei, Peta C. Bonham‐Smith, Edel Pérez‐López

Bibliographic record

VenuePlant Health Progress · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversity of SaskatchewanUniversity of Calgary
FundersSaskatchewan Canola Development CommissionMinistry of Agriculture - Saskatchewan
KeywordsClubrootBiologyObligate parasiteObligateBrassicaDisease managementAgronomyHost (biology)BotanyEcologyMEDLINE

Abstract

fetched live from OpenAlex

Clubroot is a devastating disease affecting cruciferous crops worldwide. Clubroot was first described in the 13th century in Russia and from that moment has been affecting European, Asian, and American brassica production. Plasmodiophora brassicae is the clubroot causal agent, and it is an obligate intracellular parasite that, as soil-borne resting spores, can remain viable in soil for many years. This persistence in the soil is a major negative contributing factor to the management of clubroot disease and highlights the importance for brassica growers to have ready access to current information on the distribution of the pathogen. The interactive online tool ClubrootTracker ( http://clubroottracker.ca ) has been developed to enable users to view pathogen and disease presence in geographic locations across the world. ClubrootTracker, as described in this manuscript, has been developed to provide brassica farmers a tool that will contribute to clubroot management and aid in planning a clubroot-free farm. This tool is an open resource that has the main goal of acquisition of GPS information in reporting the pathogen or the disease by the researchers working with it around the world.

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)0.003
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.175
Threshold uncertainty score0.587

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.002
Science and technology studies0.0010.000
Scholarly communication0.0030.004
Open science0.0020.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1750.077

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 head0.047
GPT teacher head0.259
Teacher spread0.211 · 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
GenreSoftware

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

Citations4
Published2020
Admission routes2
Has abstractyes

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