{"id":"W4396958615","doi":"10.1061/9780784485477.089","title":"An Improved Conceptual Bayesian Model for Dam Break Risk Assessment","year":2024,"lang":"en","type":"article","venue":"","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Computer science; Bayesian probability; Conceptual model; Dam break; Bayesian network; Artificial intelligence; History; Flood myth","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":[0.00637114,0.001249572,0.001809416,0.002677545,0.0008792451,0.003496487,0.004704298,0.003417375,0.009300557],"category_scores_gemma":[0.01811949,0.001136405,0.002052512,0.002444021,0.001795567,0.004442703,0.002512619,0.003196384,0.001682702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002685615,"about_ca_system_score_gemma":0.002979173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01791296,"about_ca_topic_score_gemma":0.01552136,"domain_scores_codex":[0.9969389,0.001289107,0.0001430606,0.0005260906,0.0008480155,0.0002547662],"domain_scores_gemma":[0.9932802,0.004442067,0.0007290103,0.0002852818,0.001034632,0.0002287475],"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":[0.00006105304,0.00004209012,0.001423499,0.0001099244,0.00007402716,0.0001611746,0.0001836439,0.7845575,0.0006012843,0.1851292,0.002765924,0.02489076],"study_design_scores_gemma":[0.00001506619,0.00003308417,0.0003513256,0.00004731542,0.00004092798,0.00008420386,0.00002701044,0.9297075,0.0001199739,0.06577063,0.003767157,0.00003579681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005017347,0.0004986391,0.9870641,0.000652753,0.00005903389,0.00006518347,0.00044219,0.0001574804,0.006043239],"genre_scores_gemma":[0.5418698,0.003935096,0.4243336,0.0007687234,0.0004237445,0.0009126023,0.001770787,0.0003611213,0.0256245],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01791296,"threshold_uncertainty_score":0.03561735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00890690626313648,"score_gpt":0.255065373127432,"score_spread":0.2461584668642956,"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."}}