{"id":"W2151851636","doi":"10.1186/1471-2164-14-277","title":"A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits","year":2013,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Nitrogen and Sulfur Effects on Brassica","field":"Biochemistry, Genetics and Molecular Biology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Agriculture and Agri-Food Canada","funders":"Grains Research and Development Corporation","keywords":"Biology; Genetics; Quantitative trait locus; Genome; Doubled haploidy; Genetic diversity; Dart; Gene mapping; Genetic marker; Brassica rapa; Locus (genetics); Computational biology; Gene; Chromosome; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002718864,0.0005723793,0.0005611572,0.001724897,0.0004223343,0.0003920382,0.0005232625,0.0003308084,0.001681863],"category_scores_gemma":[0.0007253814,0.0003154862,0.0004848413,0.001067469,0.0001588477,0.0003298658,0.000643574,0.0004935274,0.001098185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004793825,"about_ca_system_score_gemma":0.0009210171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005277968,"about_ca_topic_score_gemma":0.006043911,"domain_scores_codex":[0.9996943,0.00001757515,0.00001250978,0.0001574631,0.00008405385,0.00003410721],"domain_scores_gemma":[0.9995209,0.00007977724,0.000126022,0.00003896043,0.0001521144,0.00008211379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005416888,0.00006423379,0.004687867,0.0004543472,0.00006339651,0.0003271496,0.0002336403,0.001983326,0.9083679,0.0008185061,0.0005565693,0.08190139],"study_design_scores_gemma":[0.0004311858,0.001991317,0.2820894,0.00039182,0.0007975971,0.00562023,0.0007537632,0.03348478,0.5912259,0.003969575,0.07900979,0.0002346144],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7365331,0.001979686,0.239125,0.0001604094,0.00004847856,0.0004532183,0.0142839,0.001831668,0.005584565],"genre_scores_gemma":[0.6491172,0.001296324,0.3051223,0.00006963239,0.00002568715,0.0004220429,0.03744822,0.0002169525,0.006281722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005277968,"threshold_uncertainty_score":0.01049447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01759463385482243,"score_gpt":0.2734138778097709,"score_spread":0.2558192439549485,"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."}}