{"id":"W4389096402","doi":"10.1111/ppa.13817","title":"Race typing of <i>Puccinia striiformis</i> f. sp. <i>tritici</i> using an improved differential set will accelerate genetic gains for stripe rust resistance in Canada","year":2023,"lang":"en","type":"article","venue":"Plant Pathology","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Saskatchewan; Agriculture and Agri-Food Canada; University of British Columbia","funders":"","keywords":"Puccinia striiformis; Stripe rust; Race (biology); Biology; Typing; Rust (programming language); Differential (mechanical device); Set (abstract data type); Resistance (ecology); Plant disease resistance; Genetics; Botany; Agronomy; Computer science; Gene; Engineering","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":[0.0003036689,0.0002555489,0.0003549109,0.0008833379,0.0005415102,0.0003202122,0.0003000786,0.0003394802,0.001620051],"category_scores_gemma":[0.0004306626,0.000200622,0.0004030471,0.0006258896,0.0002115228,0.0004866616,0.0003264162,0.0005551481,0.0006947069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007392766,"about_ca_system_score_gemma":0.0002669468,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01039774,"about_ca_topic_score_gemma":0.01970723,"domain_scores_codex":[0.9997892,0.00002184614,0.00002449205,0.00008052398,0.00004295985,0.00004111583],"domain_scores_gemma":[0.9996276,0.00007019071,0.00007664671,0.00005557909,0.000115806,0.00005417265],"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":[0.00009532565,0.00003949791,0.007344226,0.00003077327,0.000008529146,0.00007434589,0.0001531763,0.00005157801,0.9828909,0.0001100361,0.0001704988,0.009030968],"study_design_scores_gemma":[0.00005132722,0.0009098498,0.6101221,0.00004125757,0.0001048717,0.001561627,0.0007459817,0.001931207,0.3598633,0.0004414273,0.02415419,0.00007294533],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851763,0.000164955,0.008531431,0.0001583673,0.00004386577,0.00009862346,0.002057248,0.0002075481,0.003561595],"genre_scores_gemma":[0.9662427,0.0002831499,0.01678246,0.0002609651,0.00001809868,0.0001042136,0.01166702,0.0001377456,0.004503729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9896023,"threshold_uncertainty_score":0.02067441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04853322153064938,"score_gpt":0.2473932933903883,"score_spread":0.1988600718597389,"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."}}