{"id":"W7144922255","doi":"","title":"原子力発電所における多忠実度シミュレーションを用いた動的確率論的リスク評価","year":2022,"lang":"en","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Atomic Energy (Canada)","funders":"Japan Atomic Energy Agency","keywords":"Probabilistic logic; Importance sampling; Accident (philosophy); Sampling (signal processing); Estimation; Probabilistic risk assessment; Risk assessment; Core (optical fiber); Function (biology)","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":[0.002207262,0.0005701758,0.0005341562,0.001333726,0.0007174012,0.00157739,0.0008870207,0.0007292068,0.004605981],"category_scores_gemma":[0.005600705,0.0005742704,0.0009359319,0.0009523918,0.000929601,0.001836571,0.0009591431,0.001376615,0.001036275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009429829,"about_ca_system_score_gemma":0.001778003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004193001,"about_ca_topic_score_gemma":0.00604942,"domain_scores_codex":[0.9987698,0.0002905478,0.00009708865,0.0002459666,0.0005293144,0.00006720024],"domain_scores_gemma":[0.9972827,0.001303357,0.0003780797,0.0004364692,0.0005125707,0.00008680653],"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":[0.0001669779,0.0001745386,0.02249962,0.0003835085,0.0001395311,0.0004245845,0.000432102,0.5829541,0.0168177,0.08771592,0.004232832,0.2840585],"study_design_scores_gemma":[0.00001874304,0.0001145273,0.003609578,0.00004739509,0.00003934924,0.0002992136,0.000135866,0.9374972,0.009262847,0.03992231,0.008991796,0.00006111614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03750618,0.0002992017,0.9512761,0.0002526128,0.00005112293,0.000106028,0.0003404272,0.0005014029,0.009666914],"genre_scores_gemma":[0.5589433,0.0009420291,0.4334569,0.0001138907,0.00007649681,0.0002444301,0.001057266,0.0001855351,0.004980156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004605981,"threshold_uncertainty_score":0.01540852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07834910827151312,"score_gpt":0.3584295539129714,"score_spread":0.2800804456414583,"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."}}