{"id":"W2083847842","doi":"10.1016/j.ress.2010.12.001","title":"Availability of a general k-out-of-n:G system with non-identical components considering shut-off rules using quasi-birth–death process","year":2010,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Correctness; Redundancy (engineering); Algorithm; Monte Carlo method; Process (computing); Birth–death process; Computer science; Mathematical optimization; State (computer science); Mathematics; Applied mathematics; Reliability engineering; Engineering; Population; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001558467,0.0005727088,0.001254579,0.0001894976,0.0001040785,0.00004537521,0.0004052863,0.0003646219,0.00001216956],"category_scores_gemma":[0.000251114,0.0005250724,0.0002409017,0.0003800692,0.0002035097,0.0003648202,0.00007107572,0.0006046086,0.000008869063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005546493,"about_ca_system_score_gemma":0.0001405818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002259717,"about_ca_topic_score_gemma":0.00002447499,"domain_scores_codex":[0.9961434,0.00008464909,0.001818435,0.0006632468,0.0006351619,0.0006551084],"domain_scores_gemma":[0.997419,0.0002547406,0.0003015072,0.001199779,0.0005701598,0.0002548131],"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":[0.0001192575,0.0001282165,0.01191805,0.01848576,0.0001125907,0.000007566645,0.0004899893,0.9278223,0.03899029,0.001838069,0.000001898866,0.00008600572],"study_design_scores_gemma":[0.0007950782,0.00008540831,0.007275339,0.001927879,0.00009958995,0.00005989978,0.0002449503,0.9796202,0.009286108,0.00001175861,0.00007199794,0.0005218132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7727407,0.00005902968,0.223981,0.000006200653,0.001223453,0.0009342386,0.00008680738,0.0005750457,0.0003934865],"genre_scores_gemma":[0.9709268,0.00001228089,0.02873023,0.000001283296,0.0001240153,0.00005642554,0.00002894059,0.0001112182,0.000008791948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1981861,"threshold_uncertainty_score":0.9997201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008699082593434302,"score_gpt":0.2123598277421805,"score_spread":0.2036607451487462,"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."}}