{"id":"W2954419084","doi":"10.3390/e21070649","title":"An Effective Approach for Reliability-Based Sensitivity Analysis with the Principle of Maximum Entropy and Fractional Moments","year":2019,"lang":"en","type":"article","venue":"Entropy","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Principle of maximum entropy; Multiplicative function; Multivariate statistics; Applied mathematics; Sensitivity (control systems); Monte Carlo method; Maximum entropy probability distribution; Entropy (arrow of time); Mathematics; Computer science; Mathematical optimization; Algorithm; Statistical physics; Statistics; Mathematical analysis; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002337837,0.0001329242,0.0003422466,0.0001480331,0.00009670265,0.00005931885,0.0001863763,0.00005343566,0.00004125646],"category_scores_gemma":[0.0004347225,0.00007003518,0.0001187829,0.0005621296,0.0001322511,0.0001371178,0.00002940835,0.0001041168,0.000005473981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004917644,"about_ca_system_score_gemma":0.00004429801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001095604,"about_ca_topic_score_gemma":0.000001435048,"domain_scores_codex":[0.9981455,0.0002960566,0.0002352466,0.0004712893,0.0006672409,0.0001846401],"domain_scores_gemma":[0.9967785,0.002107122,0.0001718998,0.0005997903,0.0002666267,0.00007600751],"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":[0.0005393883,0.0002548458,0.07628676,0.00002723338,0.000221673,6.341597e-7,0.000112552,0.9128214,0.002943493,0.006324541,0.00008218498,0.0003853391],"study_design_scores_gemma":[0.0008436954,0.0003460754,0.0999431,0.000003641058,0.0001794241,0.0000014725,0.00009375195,0.8952307,0.001049399,0.001481852,0.0007089686,0.0001178764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4316294,0.000007102335,0.5676721,0.00006303988,0.00004109623,0.0005234204,0.00002746651,0.00001247537,0.00002385986],"genre_scores_gemma":[0.9678517,3.614102e-7,0.03190348,0.00003149503,0.0000387256,0.00005699523,0.00001744578,0.000008207635,0.00009161202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5362223,"threshold_uncertainty_score":0.2855952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795162497005744,"score_gpt":0.2939980294390804,"score_spread":0.276046404469023,"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."}}