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Record W2029780955 · doi:10.4141/cjps08190

Classification of canola (<i>Brassica napus</i>) winter cultivars by secondary dormancy

2009· article· en· W2029780955 on OpenAlexvenueno aff
Sabine Gruber, Katharina Emrich, Wilhelm Claupein

Bibliographic record

VenueCanadian Journal of Plant Science · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaBrassicaDormancyCultivarBiologyAgronomySeed dormancyGermination

Abstract

fetched live from OpenAlex

Secondary dormancy is the major reason for seed persistence of canola (Brassica napus L.) in the soil. Volunteers emerging from the soil seed bank can lead to unwanted gene dispersal. More than 40 B. napus canola cultivars were tested for secondary dormancy under laboratory conditions. All cultivars were classified into groups of low, medium, and high dormancy by performing a cluster analysis. The results suggest that secondary dormancy is a cultivar-specific trait. Additionally, inter-year variation in dormancy indicates that it seems to be influenced by a set of environmental factors. Among years, classification of cultivars based on relative rank was more robust than classification based on absolute dormancy values. The classification of cultivars by their dormancy level would allow farmers to select and grow low-dormancy cultivars. Knowledge about the relative secondary dormancy of the currently grown cultivars could help growers and breeders lower canola seed bank persistence. Key words: Brassica napus, cluster analysis, genotype, secondary dormancy, soil seed bank

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Plant ScienceSame topicNitrogen and Sulfur Effects on BrassicaFrench-language works237,207