{"id":"W1923533812","doi":"10.1109/isuma.1995.527682","title":"Tail effects of uncertainty modeling in QRA","year":2002,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Research Council Canada","keywords":"Reliability (semiconductor); Computer science; Risk analysis (engineering); Uncertainty quantification; Reliability engineering; Risk assessment; Engineering; Machine learning; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00602932,0.0006938653,0.0007852939,0.000914024,0.000695039,0.001929932,0.0009994698,0.001091242,0.002296644],"category_scores_gemma":[0.02318948,0.0005780747,0.0009355632,0.0007873683,0.00202814,0.003606696,0.002495295,0.002079383,0.0004343716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008180045,"about_ca_system_score_gemma":0.0005997839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002150684,"about_ca_topic_score_gemma":0.001512669,"domain_scores_codex":[0.9970013,0.001643924,0.0001409431,0.0002357903,0.0007841617,0.0001938171],"domain_scores_gemma":[0.9786955,0.01638173,0.001802736,0.001616564,0.001220188,0.0002833553],"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":[0.0001300319,0.00002648725,0.001644545,0.0001088808,0.00004794392,0.0002584017,0.0003524991,0.7722612,0.003798714,0.1934902,0.0004872469,0.02739379],"study_design_scores_gemma":[0.000004206805,0.0000541561,0.000312012,0.00002928214,0.00002182446,0.0000696909,0.00003020436,0.9018477,0.001423398,0.09520607,0.0009664377,0.00003491685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02618257,0.0006079503,0.9672638,0.0004114304,0.00004620764,0.00002615738,0.0000467979,0.0002931012,0.005122026],"genre_scores_gemma":[0.938028,0.000745178,0.05700035,0.0002131895,0.0001030256,0.00005918375,0.00004505706,0.0001691275,0.00363704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00602932,"threshold_uncertainty_score":0.03188646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.124194137227937,"score_gpt":0.3004483593726884,"score_spread":0.1762542221447514,"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."}}