{"id":"W2912787829","doi":"10.2135/cropsci2018.05.0348","title":"Mapping QTL Associated with Stripe Rust, Leaf Rust, and Leaf Spotting in a Canadian Spring Wheat Population","year":2019,"lang":"en","type":"article","venue":"Crop Science","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Alberta Ministry of Agriculture and Forestry; Agriculture Food and Rural Development; University of Alberta","funders":"Genome Prairie; Alberta Innovates; Agriculture and Agri-Food Canada; Western Grains Research Foundation; University of Alberta; Ministry of Agriculture - Saskatchewan; Genome Canada; Genome Alberta; Alberta Crop Industry Development Fund","keywords":"Quantitative trait locus; Biology; Rust (programming language); Leaf spot; Agronomy; Population; Cultivar; Resistance (ecology); Plant disease resistance; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000595037,0.00009401467,0.0001243171,0.00006129579,0.0003156688,0.000136622,0.0001800011,0.00006479127,0.00005312142],"category_scores_gemma":[0.00005529494,0.00004133686,0.00001483292,0.000779872,0.0001244277,0.0001561462,0.0000476248,0.0001059088,0.00000752008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008129142,"about_ca_system_score_gemma":0.00005177679,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1106891,"about_ca_topic_score_gemma":0.3618892,"domain_scores_codex":[0.9988487,0.00002783844,0.0001300822,0.0003377692,0.0001638827,0.0004917282],"domain_scores_gemma":[0.9996549,0.00003921831,0.00004810373,0.00004990499,0.00004528127,0.0001626293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003084537,0.000007040117,0.8305447,0.000002406902,8.132544e-7,0.000006911991,0.0001267856,0.0000489166,0.1521076,0.0001220099,0.000003976104,0.01702582],"study_design_scores_gemma":[0.0001023183,0.00009009587,0.9971375,0.00005488946,0.000001433478,0.000005850989,0.0003253742,0.0007198897,0.0006602494,0.00004279788,0.0007283631,0.0001311828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979014,0.00008639706,9.841034e-7,0.0003966326,0.00009512171,0.0001423453,0.000005358047,0.00001563926,0.001356089],"genre_scores_gemma":[0.9995023,0.00001015195,0.0001117532,0.000120293,0.00004310161,0.000002123661,0.000007256808,7.784944e-7,0.0002022645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2512001,"threshold_uncertainty_score":0.8952329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01515563708646504,"score_gpt":0.2079358776180722,"score_spread":0.1927802405316071,"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."}}