{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003108278,0.0006623625,0.0009329919,0.0007700539,0.001165431,0.004387304,0.001168796,0.001781081,0.004487051],"category_scores_gemma":[0.005354591,0.000275074,0.0007856809,0.001073013,0.002351629,0.00503479,0.004216543,0.002125091,0.0002289374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003539233,"about_ca_system_score_gemma":0.007045398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01771612,"about_ca_topic_score_gemma":0.02900569,"domain_scores_codex":[0.9988467,0.0004994985,0.00004367684,0.0001542872,0.0001340629,0.0003217325],"domain_scores_gemma":[0.9973674,0.0009838139,0.0007325388,0.0002091763,0.0003795182,0.000327526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003768509,0.0008266592,0.0744279,0.001365233,0.00100534,0.001221132,0.001213186,0.2950312,0.008914812,0.3886609,0.03080259,0.1961542],"study_design_scores_gemma":[0.00008382876,0.0004635731,0.03621466,0.0006250531,0.000290386,0.0002787122,0.00872867,0.1847997,0.006016127,0.7111614,0.05116554,0.00017236],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6539385,0.00552834,0.1686592,0.1020457,0.0007893752,0.0003482011,0.0009966606,0.0009110389,0.0667829],"genre_scores_gemma":[0.9833145,0.001283292,0.01137695,0.002471494,0.00007538441,0.00006180254,0.00009069097,0.00004291884,0.001282999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01771612,"threshold_uncertainty_score":0.03522599,"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."}}