{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004624002,0.000185869,0.000337213,0.00007889771,0.0002059454,0.00005137822,0.0001228632,0.0001485193,0.00002728735],"category_scores_gemma":[0.0004912911,0.0001931249,0.00009114422,0.0008015818,0.0001632019,0.0002631166,0.00007400628,0.0002541216,1.480992e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003204424,"about_ca_system_score_gemma":0.0002912654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009534233,"about_ca_topic_score_gemma":0.0000890814,"domain_scores_codex":[0.9984382,0.0001199071,0.0004629892,0.0003831298,0.0002150503,0.0003807249],"domain_scores_gemma":[0.9986219,0.00006822006,0.00006010973,0.0005400603,0.0006243444,0.00008535627],"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":[0.000008917632,0.00001197017,0.03122604,0.0004478891,0.00002536382,0.00000416238,0.0002898529,0.9594603,0.00258239,0.0009186558,0.000004862502,0.005019621],"study_design_scores_gemma":[0.0001076174,0.00001088204,0.01060215,0.00003473701,0.00005946893,0.000009466084,0.001267259,0.9582908,0.002836901,0.02657093,0.00002458695,0.0001851556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6573215,0.0005270969,0.3418277,0.00004180322,0.00005361734,0.0001088059,0.000003531554,0.00005415281,0.00006180587],"genre_scores_gemma":[0.9902065,0.00004540865,0.009637504,0.00001193778,0.00006609974,0.000003825434,0.000007392796,0.00001781851,0.000003547308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.332885,"threshold_uncertainty_score":0.7875404,"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."}}