{"id":"W2472083102","doi":"10.1007/s11032-016-0496-5","title":"Microsatellite markers used for genome-wide association mapping of partial resistance to Sclerotinia sclerotiorum in a world collection of Brassica napus","year":2016,"lang":"en","type":"article","venue":"Molecular Breeding","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Saskatchewan Canola Development Commission; Ministry of Agriculture - Saskatchewan; Genome Canada","keywords":"Sclerotinia sclerotiorum; Biology; Sclerotinia; Microsatellite; Brassica; Association mapping; Population; Genetics; Quantitative trait locus; Stem rot; Plant disease resistance; Germplasm; Allele; Botany; Genotype; Gene; Single-nucleotide polymorphism","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006177863,0.0001080688,0.0002340615,0.00007258355,0.00008133664,0.00001838703,0.0001351279,0.00007629633,0.00001717122],"category_scores_gemma":[0.0002089087,0.00005118643,0.000107874,0.000680959,0.00001783165,0.00005482844,0.00003406857,0.00003959609,0.000001542563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001311948,"about_ca_system_score_gemma":0.00001092225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002098976,"about_ca_topic_score_gemma":0.001354735,"domain_scores_codex":[0.9988118,0.00005579533,0.0003556511,0.0002585569,0.0002150797,0.0003031082],"domain_scores_gemma":[0.9993175,0.0002252103,0.000258649,0.00004591637,0.00009732,0.00005539978],"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":[0.0001233024,0.00002605227,0.02923625,0.00001909601,0.00001226351,0.000001572343,0.00004584468,0.000006414327,0.9688659,0.00008635767,0.0001130903,0.0014639],"study_design_scores_gemma":[0.0004714264,0.0001450436,0.2914994,0.0004394225,0.00001117858,2.891211e-7,0.00007057367,0.00001806309,0.7021137,0.0001887869,0.004867076,0.0001750264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952888,0.00005868228,0.002160792,0.001655469,0.0001082988,0.0004812033,0.0001108245,0.00001600718,0.0001198837],"genre_scores_gemma":[0.9976681,0.00001436387,0.001441395,0.00008067523,0.00003993301,0.00004000251,0.00001069808,0.000002270133,0.0007025729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2667522,"threshold_uncertainty_score":0.2087322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01752840377040166,"score_gpt":0.2034664195495179,"score_spread":0.1859380157791163,"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."}}