{"id":"W1541832321","doi":"","title":"Multiobjective Optimization in Health Care Management. A metaheuristic and simulation approach.","year":2008,"lang":"en","type":"article","venue":"Algorithmic operations research","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metaheuristic; Context (archaeology); Computer science; Mathematical optimization; Management science; Operations research; Multi-objective optimization; Quality (philosophy); Health care; Mathematics; Machine learning; Artificial intelligence; Engineering; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003181242,0.001039459,0.0009594904,0.00161532,0.0004952569,0.002088002,0.001124909,0.001713013,0.002148945],"category_scores_gemma":[0.004608487,0.0005710421,0.0009979511,0.001792307,0.002061693,0.001632449,0.001271894,0.0020971,0.0003567672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002186259,"about_ca_system_score_gemma":0.003443891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00396355,"about_ca_topic_score_gemma":0.005342407,"domain_scores_codex":[0.9979129,0.001448048,0.00006657226,0.0000977781,0.0004106198,0.00006389687],"domain_scores_gemma":[0.9978975,0.001560322,0.0001906877,0.00009963036,0.0001504945,0.0001013228],"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":[0.00002311429,0.00008048482,0.0006776045,0.0003034652,0.0002293917,0.00006311424,0.00009789562,0.5801452,0.0003284089,0.3699946,0.004459512,0.04359714],"study_design_scores_gemma":[0.00002972383,0.00006041319,0.0002923842,0.0001662505,0.0000391926,0.00005306047,0.0001189336,0.6867349,0.0002144051,0.2964988,0.01577437,0.00001759404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006033993,0.01355901,0.9490845,0.007369836,0.0004976125,0.0001464833,0.000151769,0.0001492447,0.02300759],"genre_scores_gemma":[0.341785,0.01347324,0.6325351,0.001543198,0.0007762806,0.0007013456,0.0001919224,0.0001367387,0.008857114],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00396355,"threshold_uncertainty_score":0.01682425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1406919612659554,"score_gpt":0.4994470119753868,"score_spread":0.3587550507094314,"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."}}