{"id":"W2922434677","doi":"10.1094/phyto-04-18-0124-r","title":"Meta-Analytic and Economic Approaches for Evaluation of Pesticide Impact on Sclerotinia Stem Rot Control and Soybean Yield in the North Central United States","year":2019,"lang":"en","type":"article","venue":"Phytopathology","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agricultural Research Service; Wisconsin Soybean Marketing Board; Minnesota Soybean Research and Promotion Council; Iowa Soybean Association; U.S. Department of Agriculture","keywords":"Sclerotinia sclerotiorum; Sclerotinia; Biology; Pesticide; Yield (engineering); Stem rot; Cultivar; Toxicology; Agronomy; Biotechnology; Horticulture","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008973649,0.0001042119,0.0003033899,0.00002251439,0.00004048495,0.00001633976,0.00008294504,0.00004324873,0.00002114057],"category_scores_gemma":[0.00002091601,0.00003211196,0.0000757607,0.00006153541,0.0000376173,0.0000291875,0.0000100172,0.0000550233,0.000001138091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001412811,"about_ca_system_score_gemma":0.000007617026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000565886,"about_ca_topic_score_gemma":0.001542234,"domain_scores_codex":[0.999137,0.0002203623,0.0001733284,0.0002037386,0.00008321623,0.000182306],"domain_scores_gemma":[0.999243,0.0005447291,0.000112084,0.00004894844,0.00002296473,0.00002826658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001254211,0.0003476952,0.8641769,0.00009305344,0.0006836952,0.00001049298,0.001300972,0.0197296,0.08933919,0.00645352,0.00005888169,0.01655174],"study_design_scores_gemma":[0.0005066005,0.0006207621,0.9707497,0.000005686048,0.0004834892,0.00001210879,0.0003651777,0.02563929,0.0003234899,0.001188177,0.00001633352,0.0000892186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998457,0.0001877766,0.00001094646,0.000329574,0.00002916617,0.0006575154,0.0002921436,0.000004020665,0.00003187183],"genre_scores_gemma":[0.9997123,0.00001831239,0.00001007501,0.0001157433,0.00002476254,0.00004194628,0.00006767594,7.71783e-7,0.000008435263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1065727,"threshold_uncertainty_score":0.1309488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1089749826583771,"score_gpt":0.25502748985269,"score_spread":0.1460525071943129,"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."}}