{"id":"W2966891795","doi":"10.3390/w11081701","title":"A New Metric for Assessing Resilience of Water Distribution Networks","year":2019,"lang":"en","type":"article","venue":"Water","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Metric (unit); Resilience (materials science); Risk analysis (engineering); Robustness (evolution); Redundancy (engineering); Computer science; Process (computing); Hazard; Reliability engineering; Environmental resource management; Engineering; Business; Environmental science; Operations management; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00193006,0.001070488,0.0007172587,0.004697614,0.0005750289,0.00128106,0.0008997889,0.0008665394,0.001555352],"category_scores_gemma":[0.008009607,0.0001924553,0.0006956941,0.002388072,0.0007609432,0.003054422,0.001339064,0.000667621,0.0002034582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001782945,"about_ca_system_score_gemma":0.0009361182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003755567,"about_ca_topic_score_gemma":0.003141532,"domain_scores_codex":[0.9982848,0.0004399873,0.0001729053,0.0002291156,0.0007251875,0.000148028],"domain_scores_gemma":[0.996505,0.001411295,0.0007662339,0.0002849323,0.0008106539,0.0002219635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001763104,0.0001003915,0.02142108,0.000326453,0.0002878942,0.0002135081,0.0002122764,0.8380404,0.01445878,0.02767917,0.003506873,0.09357694],"study_design_scores_gemma":[0.00001296852,0.0003463465,0.01508875,0.00008407083,0.00009279029,0.0003066292,0.000309791,0.9540895,0.006937905,0.01430089,0.008325573,0.0001048184],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1773843,0.001657429,0.8023062,0.0005305975,0.0002515799,0.0003278568,0.002835816,0.001241434,0.01346487],"genre_scores_gemma":[0.8951442,0.0004263461,0.1017728,0.00004962424,0.00005160675,0.0001813829,0.001076968,0.00006709154,0.001229992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004697614,"threshold_uncertainty_score":0.01293617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004449462296212399,"score_gpt":0.219212061446941,"score_spread":0.2147625991507286,"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."}}