{"id":"W3013574729","doi":"10.18280/jesa.520110","title":"Cloud Intelligent Logistics Service Selection Based on Combinatorial Optimization Algorithm","year":2019,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Cloud computing; Computer science; Selection (genetic algorithm); Service (business); Distributed computing; Artificial intelligence; Business; Operating system","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":[0.0008134251,0.0009700218,0.001410789,0.001566301,0.000899356,0.001776365,0.001217623,0.000887758,0.002365144],"category_scores_gemma":[0.001624858,0.0004346266,0.001116344,0.001844989,0.0005643675,0.0009997869,0.0008872764,0.0007370839,0.0002983277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709552,"about_ca_system_score_gemma":0.002170095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009918552,"about_ca_topic_score_gemma":0.005263803,"domain_scores_codex":[0.9991818,0.0002225086,0.00003923108,0.0001210817,0.0002513011,0.0001841199],"domain_scores_gemma":[0.9994172,0.0002908418,0.00006350863,0.00002937297,0.0001350162,0.00006409843],"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":[0.00007635509,0.00007856031,0.001053386,0.00005329127,0.00005238398,0.00007180082,0.00002510732,0.948917,0.0009275289,0.009540082,0.001719795,0.03748468],"study_design_scores_gemma":[0.000008661048,0.000008462207,0.00005472422,0.000001650994,0.000004462235,0.000008553698,0.000004318105,0.9984179,0.0001021412,0.001221671,0.0001652891,0.000002222412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05347831,0.0006549519,0.9344622,0.0004906917,0.0001113267,0.0002289654,0.000122408,0.0005052063,0.009945937],"genre_scores_gemma":[0.7599084,0.0005234112,0.2340308,0.0002010244,0.00007770215,0.0003623733,0.0003359442,0.00009700372,0.004463263],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009918552,"threshold_uncertainty_score":0.01972163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941667062754593,"score_gpt":0.2412588000112577,"score_spread":0.2218421293837117,"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."}}