{"id":"W2889678130","doi":"10.1029/2017wr022478","title":"A Continental‐Scale Hydroeconomic Model for Integrating Water‐Energy‐Land Nexus Solutions","year":2018,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"International Institute for Applied Systems Analysis; Global Environment Facility","keywords":"Nexus (standard); Sustainability; Scale (ratio); Climate change; Environmental resource management; Scenario analysis; Agriculture; Water resources; Investment (military); Water supply; Natural resource economics; Environmental economics; Environmental science; Business; Economics; Computer science; Geography; Environmental engineering","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":[0.0005163811,0.0004051906,0.0004650796,0.0004136253,0.0004416654,0.001382663,0.001031043,0.001190908,0.0037318],"category_scores_gemma":[0.00126292,0.0004480185,0.0006546595,0.0007629687,0.000544019,0.0008989208,0.001097959,0.0008848268,0.0002949807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001354926,"about_ca_system_score_gemma":0.00140586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0260578,"about_ca_topic_score_gemma":0.01937207,"domain_scores_codex":[0.9998504,0.00007199535,0.000007819789,0.00003149657,0.0000198921,0.00001830711],"domain_scores_gemma":[0.9995955,0.0002247891,0.00003425267,0.00003638167,0.00006125007,0.0000479323],"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":[0.000007195107,0.000007529011,0.0003215381,0.000004737858,0.000007416626,0.00001773794,0.000006404314,0.9943231,0.00009627874,0.004233658,0.0001576542,0.000816806],"study_design_scores_gemma":[0.000005796476,0.000005102665,0.0001503727,0.000002045654,0.00000324292,0.000003323377,0.00001012404,0.9976431,0.00004214684,0.001575166,0.0005565278,0.000003069362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4099372,0.0004486445,0.5016061,0.002063195,0.0001550004,0.0002633743,0.003833268,0.0004910536,0.08120218],"genre_scores_gemma":[0.9426981,0.0002831063,0.04718276,0.0001584695,0.00002852145,0.0003167679,0.0007961834,0.00008694119,0.008449186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0260578,"threshold_uncertainty_score":0.05181229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05888803686949613,"score_gpt":0.2943719072888416,"score_spread":0.2354838704193455,"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."}}