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Record W3097310660 · doi:10.1080/07060661.2020.1825015

Symptoms and distribution of blossom blight in alfalfa seed production on the Canadian Prairies

2020· article· en· W3097310660 on OpenAlexafffundvenueabout
B. D. Gossen, R. J. Howard

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
FundersCanadian Seed Growers' AssociationAlberta Crop Industry Development Fund
KeywordsBlightMedicago sativaBiologyAgronomyBotrytis cinereaSclerotiniaSclerotinia sclerotiorumBotrytisDistribution (mathematics)GeographyHorticultureMathematics

Abstract

fetched live from OpenAlex

Surveys of alfalfa (Medicago sativa L.) seed production fields on the Canadian Prairies from 1993 to 2017 demonstrated that epidemics of blossom blight caused by Botrytis cinerea Pers. and Sclerotinia sclerotiorum (Lib.) de Bary developed almost every year at some location(s). Blossom blight symptoms were prominent when epidemics were severe, but more difficult to identify when present at low levels, which likely contributes to the infrequent reporting of blossom blight in alfalfa seed production. Epidemics were observed across the entire region, from the Peace River region of northern Alberta to southern Manitoba, consistently associated with relatively cool, wet weather conditions. The widespread nature of blossom blight on alfalfa in the years following its initial diagnosis in Canada in 1993, together with the ubiquitous distribution of the pathogens involved on other crops, indicated that blossom blight was almost certainly present on alfalfa seed crops on the Canadian Prairies for many years before the initial identification. It appears likely that blossom blight continues to cause yield loss at some locations in most years.

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)0.001
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 score0.014
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.016
GPT teacher head0.167
Teacher spread0.152 · 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
Published2020
Admission routes4
Has abstractyes

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