{"id":"W2062113845","doi":"10.1139/t03-056","title":"Neural network approach to model the limit state surface for reliability analysis","year":2003,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Analysis","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nanyang Technological University","keywords":"Serviceability (structure); Limit state design; Artificial neural network; Random variable; Nonlinear system; Moment (physics); Mathematics; Reliability (semiconductor); State variable; Limit (mathematics); Applied mathematics; Computer science; Mathematical optimization; Algorithm; Engineering; Statistics; Structural engineering; Mathematical analysis; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005222094,0.0008043913,0.0005825287,0.0005913943,0.0003365865,0.000677383,0.00128126,0.001384075,0.003748826],"category_scores_gemma":[0.001201323,0.0003473994,0.0005908931,0.0007838465,0.000577366,0.001285418,0.0004806533,0.001960335,0.0008399508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008367199,"about_ca_system_score_gemma":0.000750408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007313336,"about_ca_topic_score_gemma":0.007343671,"domain_scores_codex":[0.9997544,0.00007742849,0.00001070966,0.00004541354,0.00009311813,0.00001896902],"domain_scores_gemma":[0.9996471,0.0002028329,0.00003799214,0.00001718088,0.00008656339,0.000008331563],"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":[0.00001092951,0.00001733372,0.0002182015,0.00006317715,0.0000227741,0.00003463011,0.00003302459,0.9582332,0.00112068,0.02095117,0.0006415195,0.01865335],"study_design_scores_gemma":[7.02937e-7,0.000003566964,0.00002889347,0.000003647034,0.000002171435,0.000005549376,0.000001622355,0.996085,0.0001421995,0.003238669,0.0004856403,0.000002336746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002332699,0.0005379276,0.9935604,0.0001309644,0.00003760528,0.00001963129,0.00004176406,0.0001631395,0.003175726],"genre_scores_gemma":[0.4746973,0.003291173,0.4920506,0.0002400927,0.0002264702,0.000707151,0.0003864424,0.0001846186,0.02821614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007313336,"threshold_uncertainty_score":0.01454157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213077886256849,"score_gpt":0.1957561727053258,"score_spread":0.1836253938427573,"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."}}