{"id":"W2060250681","doi":"10.1016/j.ress.2013.09.003","title":"Selective maintenance for multi-state series–parallel systems under economic dependence","year":2013,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":138,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Component (thermodynamics); Series and parallel circuits; Reliability engineering; Series (stratigraphy); State (computer science); Maintenance actions; Resource (disambiguation); Computer science; Genetic algorithm; Mathematical optimization; Operations research; Engineering; Algorithm; Mathematics","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":[0.0007406874,0.0004884809,0.0006620579,0.000107097,0.0001350867,0.0001405908,0.0003448134,0.0002461205,0.00001361066],"category_scores_gemma":[0.0001479451,0.0004825489,0.0002065775,0.0001980043,0.00005726132,0.000782705,0.00003853159,0.0002996296,0.0001773325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002185208,"about_ca_system_score_gemma":0.00008209629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003632115,"about_ca_topic_score_gemma":0.00003253652,"domain_scores_codex":[0.9973232,0.00005658809,0.0009789119,0.0006432449,0.0001790086,0.0008190967],"domain_scores_gemma":[0.9983997,0.000213954,0.0001168467,0.0007400704,0.0003091508,0.0002203111],"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":[0.00003328842,0.00001810796,0.0001436226,0.001800223,0.00006701957,6.853465e-7,0.0001204215,0.9926586,0.000615728,0.003922698,0.0005035792,0.0001160386],"study_design_scores_gemma":[0.0007420866,0.00005288457,0.002980442,0.0003076289,0.00002078483,0.0000298571,0.0002291349,0.9927999,0.0002952902,0.00008244839,0.001910784,0.0005487453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01755951,0.0002559375,0.9745073,0.00008697274,0.002211937,0.003166289,0.0001246444,0.001578704,0.000508746],"genre_scores_gemma":[0.9657511,0.0001514873,0.03169194,0.000009559824,0.0001330708,0.001399431,0.00003698865,0.00013564,0.000690744],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9481916,"threshold_uncertainty_score":0.9997626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007771529503925715,"score_gpt":0.1949150969736654,"score_spread":0.1871435674697397,"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."}}