{"id":"W4306409156","doi":"10.1049/gtd2.12625","title":"An exact MILP model for joint switch placement and preventive maintenance scheduling considering incentive regulation","year":2022,"lang":"en","type":"article","venue":"IET Generation Transmission & Distribution","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Université Laval","funders":"","keywords":"Preventive maintenance; Incentive; Scheduling (production processes); Computer science; Joint (building); Mathematical optimization; Operations research; Business; Reliability engineering; Engineering; Microeconomics; Economics; Mathematics; Civil engineering","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":[0.0004740853,0.0001756222,0.0001668117,0.00005119997,0.0005294061,0.00006604205,0.00005801134,0.0000722044,0.0000500187],"category_scores_gemma":[0.00002584758,0.0001906834,0.00006355306,0.0001351932,0.00002875353,0.0004069375,0.0000152108,0.0001417048,5.204367e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003764316,"about_ca_system_score_gemma":0.00005110722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004103938,"about_ca_topic_score_gemma":0.000003353615,"domain_scores_codex":[0.9987345,0.00007910644,0.0003836072,0.0003467547,0.0002189624,0.0002371201],"domain_scores_gemma":[0.9995015,0.00001964456,0.00008256634,0.0001578642,0.0001444731,0.00009400626],"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":[0.00006809444,0.00005173242,0.00001595779,0.00005498404,0.00001353667,2.350904e-7,0.0006995465,0.8704142,0.1220592,0.0008528351,0.0005992886,0.005170369],"study_design_scores_gemma":[0.0008183938,0.0001029686,0.0001390805,0.00003552677,0.00003002451,0.000002985583,0.0003713637,0.9604403,0.03585657,0.001069817,0.0009175429,0.0002153798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1779134,0.0001367606,0.8204945,0.0002000372,0.0001609124,0.0007350182,0.0002128918,0.0001293334,0.00001711644],"genre_scores_gemma":[0.9700446,0.0001680802,0.02634147,0.00003472458,0.00005538488,0.0003652717,0.002893924,0.00002516822,0.00007142507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.794153,"threshold_uncertainty_score":0.7775844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01979009038351595,"score_gpt":0.2329326396629384,"score_spread":0.2131425492794224,"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."}}