{"id":"W16749183","doi":"10.1016/s0097-8485(96)80011-8","title":"New Fuzzy Performance Indices for Reliability Analysis of Water Supply Systems","year":2003,"lang":"en","type":"article","venue":"Computers & Chemistry","topic":"Water Systems and Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Institute for Catastrophic Loss Reduction","keywords":"Reliability (semiconductor); Reliability engineering; Fuzzy logic; Computer science; Water supply; Risk analysis (engineering); Environmental science; Engineering; Business; Artificial intelligence; Environmental engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001213615,0.0001084946,0.0002481854,0.00004291297,0.00002520261,0.00002861462,0.0001152975,0.00007744296,0.00001627525],"category_scores_gemma":[0.000003787874,0.00008949315,0.00008913242,0.0001606846,0.00001058476,0.00007417356,0.00001148688,0.00004393069,0.00000161461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004081898,"about_ca_system_score_gemma":0.00001052339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001740186,"about_ca_topic_score_gemma":9.344524e-7,"domain_scores_codex":[0.9993367,0.00000683725,0.0002643553,0.00014738,0.00008470727,0.0001600194],"domain_scores_gemma":[0.9996056,0.00001952206,0.0000371736,0.0002353282,0.00004658375,0.00005582213],"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":[0.000003322902,0.000007470766,0.004995077,0.0008795515,0.0002295261,2.410569e-7,0.0002930144,0.9870622,0.003974654,0.000006833228,0.002389452,0.0001586261],"study_design_scores_gemma":[0.0003594226,0.00001350369,0.001031274,0.00007044905,0.0002214204,0.000002752053,0.00003811266,0.7031443,0.2873859,0.000007286902,0.007506532,0.0002191038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8666686,0.0001876338,0.1308396,0.000006809661,0.0004333303,0.000144115,0.00001270941,0.00009375583,0.001613464],"genre_scores_gemma":[0.9956477,0.000008450607,0.003756733,0.000002399926,0.00006562476,0.00001153931,0.00007618084,0.00001278223,0.0004185807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.283918,"threshold_uncertainty_score":0.3649425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005029065037162939,"score_gpt":0.173828817027905,"score_spread":0.168799751990742,"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."}}