{"id":"W2081767320","doi":"10.1142/s0218539308003143","title":"OPTIMAL DESIGN OF BINARY WEIGHTED k-OUT-OF-n SYSTEMS","year":2008,"lang":"en","type":"article","venue":"International Journal of Reliability Quality and Safety Engineering","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Genetic algorithm; Tabu search; Reliability (semiconductor); Binary number; Mathematical optimization; Computer science; Key (lock); Computation; Algorithm; Function (biology); Optimal design; Process (computing); Value (mathematics); Reliability engineering; Mathematics; Engineering; Arithmetic","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001337108,0.001044733,0.001369503,0.0007223499,0.000657331,0.001294338,0.001242677,0.001171572,0.002981875],"category_scores_gemma":[0.003351876,0.0005982182,0.0005149733,0.0005244426,0.0009036878,0.001122761,0.001101161,0.0005018933,0.0003993754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000985426,"about_ca_system_score_gemma":0.0009011358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002074921,"about_ca_topic_score_gemma":0.002516915,"domain_scores_codex":[0.9987631,0.000390283,0.00006104756,0.000261015,0.0003133283,0.0002111467],"domain_scores_gemma":[0.9988229,0.0004053311,0.0003629122,0.00006508848,0.000258436,0.00008542536],"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":[0.0003111658,0.00008388311,0.0006007856,0.0002515328,0.0000572372,0.0001354424,0.00009287654,0.9480435,0.007287269,0.01129284,0.0005922734,0.03125121],"study_design_scores_gemma":[0.00005162377,0.0001666779,0.0003014755,0.00002018965,0.0000250647,0.00004091787,0.00002907578,0.9912271,0.001488405,0.005860385,0.0007751689,0.00001392411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1420155,0.0006592036,0.844388,0.0003253687,0.0001257007,0.0001926154,0.00009809504,0.000261503,0.01193395],"genre_scores_gemma":[0.925014,0.0002146357,0.07100825,0.00008155755,0.00003241219,0.000157293,0.00006872231,0.00004817213,0.00337498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002981875,"threshold_uncertainty_score":0.009975374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02318497331536137,"score_gpt":0.2511000430412425,"score_spread":0.2279150697258811,"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."}}