{"id":"W2163232988","doi":"10.1109/ccece.1999.804927","title":"Selective maintenance optimization for multi-state systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"State (computer science); Minification; Computer science; Integer programming; Mathematical optimization; Component (thermodynamics); Sequence (biology); Series (stratigraphy); Nonlinear programming; Optimization problem; Nonlinear system; Distributed computing; Algorithm; Mathematics","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":[0.0001602925,0.0001022106,0.0001146471,0.00003856524,0.00004730745,0.00003462352,0.00004494913,0.00005157055,0.00001721891],"category_scores_gemma":[0.0001377945,0.00009215605,0.00003579976,0.0001443116,0.00001502012,0.0001563491,0.000002594826,0.00004844459,0.000008187332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009905773,"about_ca_system_score_gemma":0.00001397284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008092215,"about_ca_topic_score_gemma":0.000007220872,"domain_scores_codex":[0.9994014,0.00001781068,0.0001716457,0.0001411685,0.00005051444,0.0002174969],"domain_scores_gemma":[0.999631,0.00003030624,0.00002202878,0.0001142458,0.0001631088,0.00003926233],"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":[0.000004556112,0.00001214763,0.00002606007,0.00006660791,0.00001214848,1.25806e-7,0.00006756653,0.9933749,0.00009600308,0.004555365,0.001617888,0.0001665889],"study_design_scores_gemma":[0.0004441361,0.00002022995,0.00001541085,0.0000175264,0.000004496844,0.000002089929,0.0000775779,0.9938094,0.001378189,0.0001214578,0.003980167,0.0001293099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004787344,0.00008716547,0.9907736,0.00001099763,0.0004367352,0.0006043273,0.000007728736,0.0002943051,0.007306457],"genre_scores_gemma":[0.5418567,0.0002880402,0.4522761,0.00004870042,0.00002710311,0.0003554446,0.00002447992,0.00006289178,0.0050606],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.541378,"threshold_uncertainty_score":0.3758014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488163669256389,"score_gpt":0.2224213448412019,"score_spread":0.207539708148638,"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."}}