{"id":"W2103635361","doi":"10.1139/g10-082","title":"Design of a<i>Brassica rapa</i>core collection for association mapping studiesThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.","year":2010,"lang":"en","type":"article","venue":"Genome","topic":"Nitrogen and Sulfur Effects on Brassica","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science and Technology Planning Project; Wageningen University and Research; Chinese Academy of Agricultural Sciences; Ministry of Science and Technology of the People's Republic of China; Chinese Academy of Sciences; Koninklijke Nederlandse Akademie van Wetenschappen","keywords":"Biology; Brassica rapa; Germplasm; Association mapping; Population; Allele; Genetic diversity; Selection (genetic algorithm); Genetics; Genetic association; Genome-wide association study; Genotyping; Brassica; Evolutionary biology; Gene; Botany; Genotype; Single-nucleotide polymorphism","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003639772,0.0006566153,0.001002719,0.002509426,0.001715341,0.0008037994,0.001213595,0.0005699815,0.006270767],"category_scores_gemma":[0.00236823,0.0007525922,0.0008101267,0.002150363,0.0005517128,0.0002474888,0.001497427,0.0008794239,0.00316189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006757739,"about_ca_system_score_gemma":0.002006617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005637016,"about_ca_topic_score_gemma":0.01333323,"domain_scores_codex":[0.9968348,0.001117247,0.0002795977,0.0008494243,0.0006193499,0.0002995161],"domain_scores_gemma":[0.9962494,0.0003747001,0.0003791951,0.001181569,0.001080616,0.0007345723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008029508,0.004780293,0.04337323,0.0008409597,0.0006486035,0.001000665,0.001817158,0.001952838,0.7889159,0.005143732,0.01131299,0.1321841],"study_design_scores_gemma":[0.005313619,0.01862401,0.4520416,0.0004206055,0.001600777,0.002301698,0.001505446,0.01089997,0.1827578,0.002338773,0.3217926,0.0004031667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.63258,0.001713672,0.2138597,0.0006120855,0.0005115619,0.09621747,0.03727847,0.001552748,0.01567419],"genre_scores_gemma":[0.3103556,0.001558426,0.4674148,0.002799351,0.0002423973,0.1224892,0.07688402,0.001045163,0.01721098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006270767,"threshold_uncertainty_score":0.0209778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588361088497837,"score_gpt":0.2316858464055616,"score_spread":0.2158022355205833,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}