{"id":"W2999099692","doi":"10.3390/su12020631","title":"Sustainability Ranking of Desalination Plants Using Mamdani Fuzzy Logic Inference Systems","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Desalination; Sustainability; Water desalination; Ranking (information retrieval); Adaptability; Flexibility (engineering); Fuzzy logic; Fuzzy inference system; Engineering; Adaptive neuro fuzzy inference system; Environmental economics; Computer science; Fuzzy control system; Mathematics; Artificial intelligence; Ecology; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007034242,0.0002213855,0.0003489659,0.00002520904,0.0002064003,0.00004159948,0.0003070504,0.0001323264,0.000197231],"category_scores_gemma":[0.001159022,0.0002098736,0.0001015449,0.0003343343,0.0004923171,0.0004930357,0.0004102191,0.0001965814,0.00001176169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003329232,"about_ca_system_score_gemma":0.0001553886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002419625,"about_ca_topic_score_gemma":0.00001888335,"domain_scores_codex":[0.9976778,0.0003399313,0.0004940858,0.0004759806,0.0005446451,0.0004675418],"domain_scores_gemma":[0.999019,0.0001189949,0.0002489209,0.0003106878,0.00008928525,0.0002131636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001003081,0.0002813546,0.9648277,0.0004508077,0.000017922,0.00001596132,0.003233074,0.02378536,0.002496002,0.001818548,0.00003225209,0.002940708],"study_design_scores_gemma":[0.0009641344,0.0003975176,0.8951152,0.00002626862,0.00005529184,0.000004229831,0.01641507,0.01643991,0.001522196,0.06800539,0.0004425395,0.0006122386],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992052,0.00003707593,0.005060932,0.0006705197,0.00009437864,0.0009467828,0.00001890804,0.00005520191,0.00106423],"genre_scores_gemma":[0.9994567,0.000006058117,0.0002987168,0.0001097178,0.00003960816,0.00001847325,0.000009904926,0.00001465943,0.0000461821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06971248,"threshold_uncertainty_score":0.8705825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02994246417186682,"score_gpt":0.3177248581867824,"score_spread":0.2877823940149156,"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."}}