{"id":"W3014338003","doi":"10.1371/journal.pone.0230855","title":"Mapping quantitative trait loci associated with leaf rust resistance in five spring wheat populations using single nucleotide polymorphism markers","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Ministry of Agriculture and Forestry; Agriculture Food and Rural Development; Global Institute for Water Security; Millar College of the Bible; University of Alberta; University of Saskatchewan; Agriculture and Agri-Food Canada","funders":"Genome Prairie; Agriculture and Agri-Food Canada; Western Grains Research Foundation; Saskatchewan Wheat Development Commission; Ministry of Agriculture - Saskatchewan; Genome Canada","keywords":"Quantitative trait locus; Doubled haploidy; Biology; Rust (programming language); Locus (genetics); Single-nucleotide polymorphism; Cultivar; Genetics; Botany; Genotype; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003619682,0.0003810185,0.0002802291,0.001122729,0.0006847098,0.0004114916,0.0004248838,0.0001775239,0.0004393633],"category_scores_gemma":[0.0003904215,0.0001876176,0.0003389331,0.0009202715,0.0003160645,0.000072846,0.0002799338,0.0003151925,0.00007117493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00413744,"about_ca_system_score_gemma":0.003395317,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5549973,"about_ca_topic_score_gemma":0.8065208,"domain_scores_codex":[0.9995739,0.00002571611,0.00002463702,0.0001446746,0.0001507552,0.00008035531],"domain_scores_gemma":[0.9996274,0.00005048184,0.0000493105,0.00002008266,0.000161394,0.00009134683],"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":[0.0008355588,0.0002087692,0.2637532,0.0001195474,0.0002279294,0.0004347747,0.002920412,0.001075228,0.6844767,0.0003112243,0.0003807599,0.0452559],"study_design_scores_gemma":[0.00002497199,0.0001382396,0.9922983,0.000006132351,0.00006151086,0.00009475422,0.0004379139,0.0005780177,0.005062074,0.00002358115,0.001259058,0.00001542725],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984967,0.00007161498,0.0004374644,0.00001266347,0.000002656815,0.00003171129,0.0004519964,0.00001497657,0.000480287],"genre_scores_gemma":[0.9928865,0.0001266747,0.002844746,0.0000305279,0.000001521419,0.00004450314,0.002446812,0.00001597236,0.00160273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5549973,"threshold_uncertainty_score":0.8952469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1211323300154514,"score_gpt":0.2314780864689397,"score_spread":0.1103457564534883,"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."}}