{"id":"W4385949184","doi":"10.3390/ijerph20166593","title":"Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network","year":2023,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Stormwater; Resilience (materials science); Critical infrastructure; Hazard; Green infrastructure; Bayesian network; Environmental science; Environmental planning; Environmental resource management; Computer science; Civil engineering; Engineering; Surface runoff; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002180997,0.000134184,0.0002243838,0.0005232938,0.0002539645,0.0001756173,0.0004309404,0.00007594563,0.0001661278],"category_scores_gemma":[0.00006257084,0.000114146,0.00007365851,0.0003731113,0.0002210644,0.0004853267,0.0001472481,0.0007440986,0.000008438641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009443865,"about_ca_system_score_gemma":0.0002844276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002157509,"about_ca_topic_score_gemma":0.00001451436,"domain_scores_codex":[0.9971761,0.0002023468,0.00051186,0.0001751382,0.001291716,0.0006429028],"domain_scores_gemma":[0.9991109,0.0001315986,0.0001087766,0.0001427475,0.00008174429,0.0004242553],"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":[0.00003487829,0.0001138461,0.06983287,0.00005572866,0.000310243,0.0001218019,0.0006444917,0.7557581,0.003399209,0.0001702194,0.008127089,0.1614315],"study_design_scores_gemma":[0.0009781672,0.0006145898,0.3572225,0.0001776424,0.000009214312,0.0002514879,0.002742304,0.5771002,0.0001715046,0.005843505,0.05450986,0.0003790995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810898,0.0003310306,0.01488655,0.002821446,0.0004468218,0.0001088728,0.00003846219,0.0000239646,0.0002530416],"genre_scores_gemma":[0.9949569,0.002682623,0.001431788,0.000228372,0.0006221171,0.000002356184,0.00002507653,0.00001730841,0.00003348687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2873896,"threshold_uncertainty_score":0.465474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02732013516415529,"score_gpt":0.3433111604606989,"score_spread":0.3159910252965437,"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."}}