{"id":"W3124078194","doi":"","title":"United States And Canadian Agricultural Herbicide Costs: Impacts On North Dakota Farmers","year":2001,"lang":"en","type":"article","venue":"Agribusiness & Applied Economics Report","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Acre; Canola; Agricultural economics; Economic impact analysis; Net farm income; Agriculture; Farm income; Agricultural science; Business; Economics; Geography; Agronomy; Environmental science; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002988053,0.0003036107,0.0001811971,0.001073412,0.00150893,0.00110299,0.0004970856,0.00043436,0.006132053],"category_scores_gemma":[0.001627184,0.0001553145,0.0003908441,0.002428043,0.000360845,0.0003769389,0.0005155022,0.0003554351,0.0003388612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03541564,"about_ca_system_score_gemma":0.02527756,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9897369,"about_ca_topic_score_gemma":0.9962204,"domain_scores_codex":[0.999283,0.00007268253,0.00001939609,0.00004697143,0.0003669916,0.0002109241],"domain_scores_gemma":[0.9984972,0.00009939026,0.0001751715,0.00002275399,0.0009903489,0.0002150615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001815917,0.0004266719,0.626044,0.0007593515,0.0005343397,0.001612599,0.001730266,0.008282625,0.005728678,0.009082581,0.1745727,0.1694103],"study_design_scores_gemma":[0.00007833678,0.00008412688,0.9399016,0.0001397429,0.0002063413,0.0002132054,0.002979345,0.001864339,0.0009674412,0.0004420019,0.05308081,0.00004267041],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.86621,0.005108947,0.0001772687,0.01079371,0.00009750991,0.0001666249,0.02172442,0.00006992105,0.09565166],"genre_scores_gemma":[0.9410951,0.009071787,0.0005556282,0.0013507,0.00002638665,0.00008220674,0.005963164,0.00002646656,0.04182873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03541564,"threshold_uncertainty_score":0.2569596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01228152100745236,"score_gpt":0.1962797140972641,"score_spread":0.1839981930898117,"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."}}