{"id":"W1992923086","doi":"10.1002/qre.859","title":"Optimizing the performance of a repairable system under a maintenance and repair contract","year":2007,"lang":"en","type":"article","venue":"Quality and Reliability Engineering International","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Reliability engineering; Context (archaeology); Horizon; Computer science; Time horizon; Meaning (existential); Operations research; Risk analysis (engineering); Engineering; Business; Mathematical optimization; 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":[0.002210599,0.0001509145,0.0002171608,0.00006209997,0.00006684718,0.00002664018,0.0001240164,0.0001027537,0.000006174512],"category_scores_gemma":[0.000234882,0.0001166049,0.00007353631,0.0001146443,0.0001110644,0.0002103754,0.00004513799,0.0002227477,7.972688e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001348955,"about_ca_system_score_gemma":0.00001221611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006463059,"about_ca_topic_score_gemma":0.00000669504,"domain_scores_codex":[0.9987688,0.00002553299,0.0005515846,0.0002218117,0.0002073782,0.0002249136],"domain_scores_gemma":[0.9991105,0.0003476123,0.00007300937,0.0002585326,0.0001478685,0.00006248961],"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":[0.00007928367,0.0000322973,0.004823412,0.001106912,0.00008036464,0.000001449071,0.0005679225,0.9658861,0.00150687,0.02527433,0.0000457913,0.0005952429],"study_design_scores_gemma":[0.0003211091,0.00003554679,0.06471093,0.0002109235,0.00001461041,0.00002574318,0.0003164863,0.93213,0.0009704644,0.00005160179,0.001048287,0.0001642359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9117765,0.0002773656,0.08561441,0.0002416343,0.0005397212,0.0002219458,0.00001129343,0.0003671189,0.0009500066],"genre_scores_gemma":[0.989468,0.0002980284,0.01005933,0.00003301003,0.0000576198,0.00001236983,0.000005021794,0.0000159608,0.00005066952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07769149,"threshold_uncertainty_score":0.4755011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008801323296122262,"score_gpt":0.227059277264033,"score_spread":0.2182579539679107,"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."}}