{"id":"W2099304133","doi":"10.1109/ccece.1996.548121","title":"Flexible generator maintenance scheduling considering uncertainties of objectives and parameters","year":2002,"lang":"en","type":"article","venue":"","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Robustness (evolution); Computer science; Reliability engineering; Scheduling (production processes); Fuzzy set; Fuzzy logic; Mathematical optimization; Operations research; Engineering; Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008791081,0.0006748044,0.0008335413,0.0004228963,0.0004778709,0.0006178054,0.0009229344,0.0005600295,0.0006256543],"category_scores_gemma":[0.001625769,0.0003359845,0.00052389,0.0006273345,0.000441791,0.0009008414,0.0006021042,0.000736895,0.0001489978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005168195,"about_ca_system_score_gemma":0.0005542038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001107103,"about_ca_topic_score_gemma":0.001682766,"domain_scores_codex":[0.999508,0.0001623117,0.0000223738,0.0001000017,0.000132979,0.00007430107],"domain_scores_gemma":[0.999272,0.0003736646,0.000129336,0.0001189695,0.00005934532,0.00004668376],"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":[0.00008206165,0.00001786208,0.000225251,0.00002743719,0.00002705753,0.0001033218,0.00005332668,0.9548151,0.004065354,0.007150657,0.0002462407,0.03318636],"study_design_scores_gemma":[0.00001526487,0.00003432373,0.0001420062,0.00000327031,0.000009391661,0.0000334188,0.000008162619,0.9910935,0.0009503554,0.007346135,0.0003573058,0.000006927889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05059639,0.0002014186,0.9473409,0.00007138475,0.00002380818,0.00002476618,0.00004638666,0.0001403094,0.0015546],"genre_scores_gemma":[0.9251845,0.0001308621,0.07394275,0.00001859223,0.00003852827,0.00004254936,0.00007084493,0.00003993157,0.0005314939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001107103,"threshold_uncertainty_score":0.004649222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01837379248420311,"score_gpt":0.2009022184663039,"score_spread":0.1825284259821007,"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."}}