{"id":"W2078271570","doi":"10.1115/fedsm-icnmm2010-31027","title":"Application of Uncertainty Analysis in the Comparison of Void Fraction Calculations With Experiment","year":2010,"lang":"en","type":"article","venue":"","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Power Generation","funders":"","keywords":"Uncertainty analysis; Loss-of-coolant accident; Computer science; Propagation of uncertainty; Uncertainty quantification; Source code; Sensitivity analysis; Range (aeronautics); Algorithm; Data mining; Simulation; Engineering; Machine learning; Coolant","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":[0.01504699,0.0006192098,0.0007153967,0.003073376,0.0006646623,0.001535547,0.001524476,0.0009171003,0.001596426],"category_scores_gemma":[0.05422626,0.0003964682,0.000806223,0.001434025,0.001086767,0.00191659,0.001154485,0.000818871,0.0001917406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196724,"about_ca_system_score_gemma":0.001253918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095968,"about_ca_topic_score_gemma":0.001160875,"domain_scores_codex":[0.9896651,0.004563147,0.0006253118,0.0006773428,0.004229966,0.0002392411],"domain_scores_gemma":[0.9368519,0.05303409,0.001737056,0.005052322,0.003183267,0.0001413817],"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":[0.001620932,0.0004088825,0.02340019,0.0004876147,0.0002999209,0.0002159314,0.0006908956,0.7823325,0.02734908,0.03392828,0.0007263963,0.1285393],"study_design_scores_gemma":[0.0000889446,0.0008853158,0.01430174,0.00008232443,0.0000597642,0.0001901394,0.0003095763,0.9123825,0.05085944,0.01545078,0.005243313,0.0001461817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3091767,0.0005691062,0.676806,0.0001794911,0.0001021102,0.000387543,0.0006422898,0.001531777,0.01060497],"genre_scores_gemma":[0.9044656,0.00009527047,0.09461201,0.00002366136,0.00001446626,0.0002323826,0.0002051004,0.0001158033,0.0002358437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01504699,"threshold_uncertainty_score":0.07957703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006917834452053668,"score_gpt":0.2537983799568123,"score_spread":0.2468805455047586,"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."}}