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Record W2040922380 · doi:10.1080/07060661.2013.870606

Clubroot, a persistent threat to Swedish oilseed rape production

2014· article· en· W2040922380 on OpenAlexvenueno aff
Ann-Charlotte Wallenhammar, Charlotta Almquist, Arne Schwelm, Jonas Roos, Katarzyna Marzec-Schmidt, Anders Jonsson, Christina Dixelius

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsClubrootBrassicaBiologyAgronomyOutbreakLimitingBrassica rapaCropBiotechnologyCrop rotationEngineering

Abstract

fetched live from OpenAlex

Brassica oilseed crops have been grown by Swedish farmers since the early 1940s. Years of high market prices for vegetable oils resulted in intensive cultivation of Brassica oilseeds in various regions, which led to problems with soilborne pathogens including Plasmodiophora brassicae. This pathogen most likely was present in Swedish soils prior to the Brassica oilseed boom after World War II. Currently, reports of clubroot disease outbreaks in Sweden are frequent, with a trend of increasing incidence. Since 2012, DNA-based soil analyses for the presence of P. brassicae have been offered to farmers in order to improve their crop rotation planning. Other means of limiting the damage caused by P. brassicae also are presently under study, such as the effects of boron or different sources of nitrogen. The distribution and identification of different pathotypes/races of P. brassicae in Sweden could so far not be verified. To aid in race diagnostics, resistance breeding efforts, and in understanding the biology of this Plasmodiophorid, the sequencing of the P. brassicae genome has been initiated in Sweden.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.177
Teacher spread0.164 · 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

Citations25
Published2014
Admission routes1
Has abstractyes

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