{"id":"W2766237696","doi":"10.1016/j.ecolind.2017.10.027","title":"Monte Carlo simulation based interval chance-constrained programming for regional ecosystem management – A case study of Zhuhai, China","year":2017,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Water resources management and optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; National Key Research and Development Program of China","keywords":"Ecosystem services; Environmental science; Ecosystem; Environmental resource management; Sustainability; Land use; Land-use planning; Land reclamation; Constraint (computer-aided design); Geography; Ecology; Engineering; Civil 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":[0.00186871,0.000695473,0.0008884087,0.0009068837,0.0008415715,0.001416956,0.001215944,0.00123948,0.001949449],"category_scores_gemma":[0.00289382,0.000523785,0.0007233715,0.001322543,0.0007391607,0.0007978639,0.0007408483,0.0006356839,0.0000773776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002557442,"about_ca_system_score_gemma":0.002937234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1028446,"about_ca_topic_score_gemma":0.07484319,"domain_scores_codex":[0.9993793,0.0003364247,0.00002347757,0.00008520015,0.00006378854,0.0001119146],"domain_scores_gemma":[0.9972522,0.002155006,0.0001629865,0.00006932451,0.0002338984,0.0001267144],"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":[0.00002188057,0.00003132531,0.001190389,0.000009461684,0.00001038543,0.00007837825,0.000019136,0.9954557,0.00007364232,0.001318341,0.00009742875,0.001693898],"study_design_scores_gemma":[0.000003759902,0.000007583117,0.0002480796,0.000001208707,0.000003605986,0.000004539925,0.00001201779,0.9992525,0.00002700716,0.0003957301,0.00004165456,0.000002246806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8696668,0.0003753355,0.1200102,0.0004359637,0.00003034912,0.0001338987,0.000290287,0.0002236312,0.008833573],"genre_scores_gemma":[0.9826962,0.00009316374,0.01570661,0.0000187132,0.000006816455,0.00005789911,0.0001141514,0.00002435858,0.001282175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1028446,"threshold_uncertainty_score":0.2044919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02832191969144619,"score_gpt":0.2663575596467768,"score_spread":0.2380356399553306,"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."}}