{"id":"W4404049391","doi":"10.1016/j.ress.2024.110630","title":"A resilience-driven emergency maintenance operation scheme optimization method based on risk","year":2024,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Fundamental Research Funds for the Central Universities; Natural Science Fund for Distinguished Young Scholars of Shandong Province; Taishan Scholar Project of Shandong Province; Ministry of Industry and Information Technology of the People's Republic of China; National Natural Science Foundation of China","keywords":"Resilience (materials science); Scheme (mathematics); Risk analysis (engineering); Reliability engineering; Computer science; Operations research; Engineering; Business; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001363282,0.0003975858,0.0004436975,0.0002834092,0.0001667876,0.00009518217,0.0002793092,0.0002282098,0.0002109451],"category_scores_gemma":[0.0003550145,0.0003572717,0.0002863776,0.0009859783,0.00002671963,0.0003296017,0.00002071425,0.0005528851,0.00006923788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009212492,"about_ca_system_score_gemma":0.00006408054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005158752,"about_ca_topic_score_gemma":0.000006752613,"domain_scores_codex":[0.9974079,0.000173203,0.0008234064,0.0006758163,0.000451189,0.000468536],"domain_scores_gemma":[0.998612,0.0002604759,0.00005030336,0.0008086707,0.0001226248,0.0001458783],"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":[0.00001716766,0.00001282131,0.0005906134,0.001218949,0.00004761035,0.000005036985,0.00008955537,0.9947685,0.0007512226,0.0009579799,0.0001421247,0.001398437],"study_design_scores_gemma":[0.0001374642,0.00004230659,0.00121882,0.0003897336,0.00006373027,0.000005711783,0.00004711407,0.995761,0.0005631208,0.00001264312,0.001391493,0.0003668884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009862782,0.0001965468,0.9855653,0.00008311959,0.001199845,0.0004631675,0.00007123348,0.001560673,0.0009973012],"genre_scores_gemma":[0.8984281,0.0001201334,0.1010186,0.000006134644,0.0001975969,0.00008484199,0.00004109089,0.00006782703,0.00003560968],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8885654,"threshold_uncertainty_score":0.9998879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003054715738552914,"score_gpt":0.2155996826448564,"score_spread":0.2125449669063035,"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."}}