{"id":"W2141173738","doi":"10.1109/icsmc.1995.538043","title":"System design with deteriorative components for minimal life cycle costs","year":2002,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reliability engineering; Failure rate; Reliability (semiconductor); Computer science; System lifecycle; Maintenance engineering; Genetic algorithm; Preventive maintenance; Mean time between failures; Systems design; Series (stratigraphy); 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":[],"consensus_categories":[],"category_scores_codex":[0.00004942109,0.00009131432,0.0001185335,0.00002358699,0.00004224212,0.00002677305,0.0000523089,0.00003932627,0.00003091987],"category_scores_gemma":[0.00001531326,0.00007074727,0.00002090862,0.00006307902,0.00001856642,0.0001239817,0.000004813719,0.00003127383,0.00003035742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009009159,"about_ca_system_score_gemma":0.000003354037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005467623,"about_ca_topic_score_gemma":0.000004115517,"domain_scores_codex":[0.9995427,0.00001477748,0.0001217616,0.0001064511,0.00006339585,0.0001508784],"domain_scores_gemma":[0.99972,0.0000517598,0.00001722866,0.00009906168,0.00005220916,0.00005978504],"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":[0.0001038434,0.00004155007,0.00007653837,0.0002118737,0.00005550727,0.000002691891,0.0003936873,0.9908217,0.002278489,0.0008030491,0.003179415,0.002031642],"study_design_scores_gemma":[0.0004916113,0.000120012,0.0001608627,0.00004927624,0.000009535187,0.000003172504,0.0001897127,0.997335,0.001255726,0.000005111354,0.0002683356,0.0001116148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0445635,0.00003882193,0.9491552,0.00004165281,0.00009363455,0.0005760802,0.00000586115,0.0003049725,0.005220265],"genre_scores_gemma":[0.936828,0.000009021332,0.0628771,0.00002515857,0.00002159737,0.0000899388,0.000004278807,0.00001890401,0.0001260196],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8922645,"threshold_uncertainty_score":0.288499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02151443021097975,"score_gpt":0.1939203127999961,"score_spread":0.1724058825890164,"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."}}