{"id":"W2588422084","doi":"10.1093/acrefore/9780199389407.013.66","title":"Socioeconomic Impacts of Infrastructure Disruptions","year":2016,"lang":"en","type":"reference-entry","venue":"Oxford Research Encyclopedia of Natural Hazard Science","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Critical infrastructure; Interdependence; Resilience (materials science); Natural hazard; Business; Hazard; Natural disaster; Vulnerability (computing); Environmental planning; Risk analysis (engineering); Environmental resource management; Transport engineering; Engineering; Computer security; Computer science; Environmental science; 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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001764014,0.0004854394,0.0009958942,0.001799706,0.0003903295,0.00008738282,0.002303891,0.0005532166,0.0006009738],"category_scores_gemma":[0.001031897,0.0003405747,0.000403375,0.00184803,0.00375723,0.0008723445,0.0004865589,0.002204386,0.00003263519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008702961,"about_ca_system_score_gemma":0.002060528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005096875,"about_ca_topic_score_gemma":0.0001134104,"domain_scores_codex":[0.9946517,0.000153106,0.0009553218,0.0007454526,0.002081424,0.00141303],"domain_scores_gemma":[0.9966009,0.0006114487,0.0002712835,0.001088093,0.001035026,0.0003932808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007298353,0.00006474101,0.006567308,0.002945449,0.0003125006,0.00001343151,0.0007822239,0.002801234,0.002767621,0.001396311,0.06554849,0.9167277],"study_design_scores_gemma":[0.001687003,0.000794078,0.09508675,0.004090088,0.0003430003,0.00006949753,0.001395156,0.009902921,0.008954987,0.02684579,0.8475413,0.003289442],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3504137,0.008850882,0.0003393309,0.000243596,0.003522438,0.0009433712,0.001048185,0.0001497227,0.6344888],"genre_scores_gemma":[0.6733773,0.3201326,0.00084121,0.000007164216,0.0006078476,0.00002934143,0.0000592618,0.00005212922,0.004893121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9134383,"threshold_uncertainty_score":0.9999046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01398698190308709,"score_gpt":0.3154085673096187,"score_spread":0.3014215854065316,"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."}}