{"id":"W4386471525","doi":"10.1088/1748-9326/acf727","title":"Tackling policy leakage and targeting hotspots could be key to addressing the ‘Wicked’ challenge of nutrient pollution from corn production in the U.S.","year":2023,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"National Institute of Food and Agriculture; National Science Foundation","keywords":"Nutrient management; Environmental science; Spillover effect; Agriculture; Natural resource economics; Nutrient pollution; Production (economics); Productivity; Agricultural productivity; Nutrient; Business; Environmental resource management; Economics; Ecology","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":[0.001820697,0.0001462989,0.0001262677,0.0001719779,0.0004249355,0.00005115238,0.0003997661,0.00005568994,0.00002858004],"category_scores_gemma":[0.0001686139,0.00009989313,0.00003958501,0.0007208349,0.0008365027,0.0002308087,0.0005491318,0.000430603,0.0001046471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003999486,"about_ca_system_score_gemma":0.000007315321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001405699,"about_ca_topic_score_gemma":0.00003506928,"domain_scores_codex":[0.9972248,0.0003993631,0.0002498476,0.0004584218,0.001096494,0.0005710712],"domain_scores_gemma":[0.9993085,0.0002000734,0.0000621996,0.0003387066,0.000002231796,0.00008832414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003252424,0.000569714,0.506012,0.00004764758,0.00004096611,0.00009490793,0.07455963,0.01213577,0.3711526,0.0001708569,0.0162873,0.01860343],"study_design_scores_gemma":[0.0006165201,0.0001665184,0.9659297,0.0000990062,0.0000097988,0.000004540678,0.01266805,0.002645039,0.007296131,0.002534208,0.007731101,0.0002994137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9204313,0.00007976269,0.00002126805,0.07866023,0.00007656976,0.0005571193,0.00003033156,0.000017704,0.0001256859],"genre_scores_gemma":[0.9978239,0.0003570278,0.00006663353,0.001429782,0.0001413112,0.00006660314,0.00003952024,0.00002031191,0.00005493185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4599177,"threshold_uncertainty_score":0.4073524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05962438078314018,"score_gpt":0.3157039520259385,"score_spread":0.2560795712427983,"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."}}