{"id":"W1481577689","doi":"10.1007/978-3-540-37372-8_7","title":"Neural Networks for Reliability-Based Optimal Design","year":2007,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Reliability (semiconductor); Computer science; Artificial neural network; Reliability engineering; Function (biology); Optimal design; Systems design; Space (punctuation); Robot; Engineering; Artificial intelligence; Machine learning; Software engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004766865,0.0003317694,0.0004436793,0.0002015888,0.00008066452,0.0000220425,0.0001748289,0.0002127986,0.0000211543],"category_scores_gemma":[0.00006876206,0.0003453019,0.0001602873,0.0000703834,0.0001662885,0.00004004709,0.00002580076,0.0003601081,0.00001857116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002945371,"about_ca_system_score_gemma":0.0000270107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002284329,"about_ca_topic_score_gemma":0.00001409226,"domain_scores_codex":[0.9985077,0.00001981236,0.0006397762,0.0003302799,0.0002339899,0.0002684889],"domain_scores_gemma":[0.9977154,0.001727484,0.00008545312,0.0001532892,0.0002710524,0.00004738516],"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":[0.00006325049,0.000005753372,0.000001368455,0.0001341958,0.00008749071,0.000008388816,0.00007390534,0.9799128,2.231124e-7,0.005930262,0.0006735946,0.01310883],"study_design_scores_gemma":[0.0001331354,0.000096675,0.000001602785,0.0001657809,0.00001825167,0.00000488093,0.00005596592,0.982487,0.00001241345,0.01050789,0.006207287,0.0003091223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000009246659,0.004117046,0.9858393,0.00003297399,0.002012807,0.0007516494,0.00001741926,0.0001942052,0.007025355],"genre_scores_gemma":[0.8567036,0.0005989479,0.1187246,0.0006849157,0.002047464,0.0005154892,0.0001431678,0.0003607175,0.02022107],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8671147,"threshold_uncertainty_score":0.9998999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1003419028772211,"score_gpt":0.3359028461932594,"score_spread":0.2355609433160384,"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."}}