{"id":"W4362647392","doi":"10.1109/rams51473.2023.10088213","title":"Dynamic Multilevel Redundancy Allocation Optimization Under Uncertainty","year":2023,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Redundancy (engineering); Computer science; Reliability engineering; Process (computing); Variety (cybernetics); Key (lock); Risk analysis (engineering); Systems engineering; Industrial engineering; Operations research; Engineering; Artificial intelligence","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":[0.0001254894,0.0001026294,0.00008639952,0.0001011846,0.00005763271,0.00003048812,0.00007574102,0.0000820147,0.0001431477],"category_scores_gemma":[0.00004436997,0.00009984947,0.00003257475,0.0003816306,0.00002270425,0.0001977884,0.00001506816,0.00006785978,0.0001667315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294041,"about_ca_system_score_gemma":0.00001536949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001937697,"about_ca_topic_score_gemma":0.00002651616,"domain_scores_codex":[0.9993539,0.00001303663,0.0001788167,0.0001534981,0.0001057972,0.0001948895],"domain_scores_gemma":[0.9996525,0.00003239716,0.00001681983,0.0001868658,0.00007088748,0.00004053636],"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":[0.000002451542,0.000006922417,0.00000783621,0.00002549249,0.000008531448,2.979151e-7,0.00007858442,0.9937557,0.0004268195,0.00103559,0.001222284,0.00342949],"study_design_scores_gemma":[0.0001749276,0.000007751492,0.0006429256,0.00001543373,0.00000517072,7.929314e-7,0.0001255649,0.997589,0.0001137412,0.0008685154,0.0003296459,0.0001265167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01138858,0.00002023328,0.9816287,0.000428667,0.0003983098,0.0002144021,0.000004649337,0.001557865,0.004358618],"genre_scores_gemma":[0.9670352,0.0005156355,0.0293666,0.00007059322,0.00002039254,0.00004952043,0.000327571,0.00003969571,0.002574836],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9556466,"threshold_uncertainty_score":0.4071743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009790343237056494,"score_gpt":0.2282290386144137,"score_spread":0.2184386953773572,"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."}}