{"id":"W2922607490","doi":"10.1111/risa.13305","title":"Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System","year":2019,"lang":"en","type":"article","venue":"Risk Analysis","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Interdependence; Resilience (materials science); Hazard; Natural hazard; Probabilistic logic; Computer science; Risk analysis (engineering); Critical infrastructure; Reliability engineering; Operations research; Engineering; Geography; Computer security; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000493939,0.0002653485,0.0006917572,0.0005212172,0.00007947455,0.00004543862,0.0005014258,0.0001386462,0.0001397891],"category_scores_gemma":[0.00008015291,0.0002287266,0.0004633359,0.001329047,0.00007739702,0.0002775419,0.00006116309,0.0003131786,0.00003835867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001969783,"about_ca_system_score_gemma":0.00003191816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000176988,"about_ca_topic_score_gemma":0.0006975593,"domain_scores_codex":[0.9980156,0.0001572857,0.0006084214,0.0004479855,0.0004454905,0.0003251566],"domain_scores_gemma":[0.9984452,0.00008296373,0.0001686541,0.001024178,0.0001437125,0.0001353424],"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":[0.00001385031,0.00001551622,0.07253161,0.0001699813,0.0006563538,0.000001226644,0.0003506541,0.9217615,0.002142048,0.000118511,0.00001074501,0.002227991],"study_design_scores_gemma":[0.0001753205,0.00002847407,0.02743122,0.00002058145,0.001343898,0.000001582801,0.0006849846,0.9680388,0.001728682,0.0003082466,0.000006146201,0.0002320434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8674465,0.00005659571,0.1310719,0.000002380237,0.0000659827,0.0001742891,0.00008701817,0.0001603115,0.0009350675],"genre_scores_gemma":[0.9962516,0.00002410512,0.003576433,0.00000431253,0.00003147352,0.00001041544,0.00003943352,0.00002381789,0.0000383797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1288051,"threshold_uncertainty_score":0.9327198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003436683745686703,"score_gpt":0.1990910930350233,"score_spread":0.1956544092893366,"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."}}