{"id":"W2553813205","doi":"10.1016/j.jglr.2016.10.001","title":"Sustainable management of Great Lakes watersheds dominated by agricultural land use","year":2016,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Agricultural Statistics Service; National Institute of Food and Agriculture; Nature Conservancy of Canada; Great Lakes Protection Fund; University of Pennsylvania; Coca-Cola Foundation; Cook Family Foundation; Kellogg's; Charles Stewart Mott Foundation; Herbert H. and Grace A. Dow Foundation; National Science Foundation","keywords":"Agriculture; Investment (military); Surface runoff; Environmental resource management; Government (linguistics); Business; Adaptive management; Environmental planning; Water quality; Soil and Water Assessment Tool; Natural resource economics; Environmental science; Drainage basin; Economics; Geography; Ecology; Streamflow","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"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":[0.0003676025,0.0001805606,0.0001470802,0.0004297616,0.0007746661,0.001439249,0.0004631418,0.000367968,0.001521829],"category_scores_gemma":[0.001306726,0.0001116276,0.0002077822,0.001117265,0.001049213,0.001083131,0.001045283,0.0002498487,0.0001142756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002046873,"about_ca_system_score_gemma":0.003602109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05956987,"about_ca_topic_score_gemma":0.198741,"domain_scores_codex":[0.9998109,0.00007855556,0.000007737917,0.00003115922,0.00004626754,0.00002542972],"domain_scores_gemma":[0.9996725,0.0001019282,0.00009863679,0.00002155914,0.00004942242,0.00005582053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001513392,0.0003622983,0.4692003,0.001251011,0.0003693019,0.002091605,0.005285239,0.09910668,0.0167642,0.1041053,0.03770109,0.2636116],"study_design_scores_gemma":[0.00006766073,0.0002989133,0.6106101,0.0005496719,0.0001706157,0.0003288087,0.01564845,0.154054,0.00703019,0.08239444,0.1287158,0.0001313013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9433812,0.001937827,0.008852674,0.009978258,0.00009507455,0.00008253031,0.0005641753,0.0001960313,0.03491222],"genre_scores_gemma":[0.9887413,0.002224709,0.005603711,0.0001757408,0.00004263393,0.00003912708,0.0001802925,0.000029591,0.002962837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05956987,"threshold_uncertainty_score":0.1184462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02031346087529434,"score_gpt":0.2693591801773418,"score_spread":0.2490457193020474,"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."}}