{"id":"W2914828287","doi":"10.9753/icce.v36.papers.4","title":"PROBABILISTIC MODELING OF ABOVEGROUND STORAGE TANKS UNDER SURGE AND WAVE LOADS","year":2018,"lang":"en","type":"article","venue":"Coastal Engineering Proceedings","topic":"Water Systems and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Fragility; Finite element method; Probabilistic logic; Buckling; Surge; Structural engineering; Storm surge; Range (aeronautics); Statistical model; Wave model; Engineering; Computer science; Geology; Storm; Meteorology; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001295267,0.0001855642,0.0002141753,0.0001197202,0.00003364532,0.00005494369,0.00006449308,0.00009441582,0.000006412017],"category_scores_gemma":[0.00002690292,0.000188787,0.00002982946,0.0001879353,0.00003557545,0.0002629508,0.00004938087,0.0001093094,0.000002260284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000389795,"about_ca_system_score_gemma":0.000008332046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002221504,"about_ca_topic_score_gemma":0.0000114192,"domain_scores_codex":[0.9991763,0.000001063037,0.0002643963,0.0001789748,0.0001357133,0.0002435998],"domain_scores_gemma":[0.9996489,0.00001171927,0.00002979924,0.00007550092,0.0001526174,0.00008147737],"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":[0.000008835038,0.00001218067,0.0001000765,0.001095793,0.00004345889,0.000001548766,0.001180918,0.9866641,0.007117576,0.003338004,0.0002687495,0.0001687638],"study_design_scores_gemma":[0.0001859472,0.0000472228,0.0002506746,0.0001495266,0.00001423599,0.0000208797,0.00007539737,0.9976044,0.001139311,0.000106799,0.0001991524,0.0002065113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8088191,0.000153101,0.1881002,0.000009069204,0.0005008821,0.0001874088,0.000009147549,0.0003480639,0.0018731],"genre_scores_gemma":[0.9978052,0.00001196324,0.001730892,0.000003484763,0.000177952,0.00001247167,0.000004400536,0.00005796665,0.000195687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1889861,"threshold_uncertainty_score":0.7698512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225850896843243,"score_gpt":0.1756693694749069,"score_spread":0.1634108605064745,"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."}}