{"id":"W2199213437","doi":"10.1371/journal.pone.0145574","title":"Advancing Land-Sea Conservation Planning: Integrating Modelling of Catchments, Land-Use Change, and River Plumes to Prioritise Catchment Management and Protection","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Australian Research Council; Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación; Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, Gobierno de México; Consejo Nacional de Ciencia y Tecnología; Secretaría de Medio Ambiente y Recursos Naturales; James Cook University; Commonwealth Scientific and Industrial Research Organisation; Secretaría de Educación Pública","keywords":"Environmental science; Land use; Water quality; Biodiversity; Land use, land-use change and forestry; Land management; Eutrophication; Drainage basin; Ecosystem health; Environmental resource management; Hydrology (agriculture); Ecosystem; Water resource management; Ecosystem services; Geography; Ecology; Nutrient","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":[0.0009686679,0.0006021151,0.0007100367,0.001111759,0.0008284714,0.002223715,0.001605112,0.001240987,0.004141163],"category_scores_gemma":[0.002937133,0.0005862114,0.0009487764,0.001679196,0.0007593,0.001496655,0.001426307,0.000909062,0.0002119371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003026193,"about_ca_system_score_gemma":0.003022416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09886892,"about_ca_topic_score_gemma":0.1218806,"domain_scores_codex":[0.9997481,0.0001088019,0.00001899704,0.0000430261,0.00003655355,0.00004453221],"domain_scores_gemma":[0.9991413,0.000472129,0.0001046044,0.00005008832,0.0001160637,0.0001158085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001316981,0.00001849302,0.003315711,0.00002127192,0.00002391003,0.00003903784,0.00009299066,0.990467,0.0001759373,0.00198523,0.0002530496,0.003594178],"study_design_scores_gemma":[0.000006821328,0.000003988062,0.0005263957,0.000004375653,0.000005234639,0.000004660987,0.00004946479,0.9971678,0.00004713737,0.00168108,0.0004977256,0.000005357732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5072531,0.0005980036,0.4614488,0.002308456,0.0001076723,0.0004814087,0.002938349,0.001752012,0.02311227],"genre_scores_gemma":[0.9032809,0.0002661699,0.09267262,0.00008375759,0.00001832912,0.0002722046,0.0006693183,0.0001538702,0.002582821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09886892,"threshold_uncertainty_score":0.1965868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0947737624632913,"score_gpt":0.2333626259317857,"score_spread":0.1385888634684944,"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."}}