{"id":"W3122108246","doi":"10.3390/su13031026","title":"Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Resilience (materials science); Critical infrastructure; Community resilience; Flood myth; Hazard; Risk analysis (engineering); Bayesian network; Computer science; Natural hazard; Work (physics); Environmental resource management; Business; Engineering; Environmental science; Computer security; Geography","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":[0.001572599,0.0006164055,0.0005827625,0.001053505,0.0004729755,0.001090553,0.001248774,0.001059851,0.00189056],"category_scores_gemma":[0.004570798,0.0005111154,0.000714982,0.0008177182,0.0007398373,0.001405862,0.0008892501,0.001090996,0.0001653862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001962914,"about_ca_system_score_gemma":0.001153319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03243575,"about_ca_topic_score_gemma":0.01919692,"domain_scores_codex":[0.9994901,0.000219605,0.00002272346,0.0001141549,0.00008434966,0.00006891224],"domain_scores_gemma":[0.9981349,0.001317367,0.0002059423,0.00004325191,0.0002433207,0.00005523737],"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":[0.00001774803,0.00001068295,0.001050327,0.00001791695,0.00001328395,0.00002954721,0.00002916855,0.9910136,0.0001530861,0.004178588,0.0001480373,0.003338022],"study_design_scores_gemma":[0.000001504432,0.000006512587,0.0002250336,0.000006199869,0.000005509215,0.000005526686,0.00001160806,0.9966798,0.00005405557,0.002894591,0.0001058004,0.000003887668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1129717,0.0005146906,0.8792724,0.0008044848,0.00004030123,0.00009377718,0.0005244847,0.0001952686,0.005582879],"genre_scores_gemma":[0.9479458,0.000444064,0.04838909,0.00007235522,0.00002772174,0.0001657449,0.0003017764,0.0000172045,0.002636184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03243575,"threshold_uncertainty_score":0.06449389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006527130230617536,"score_gpt":0.2403830024898478,"score_spread":0.2338558722592302,"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."}}