{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005053696,0.0002401864,0.0002712676,0.0006210874,0.0004372854,0.0004988885,0.0003489049,0.0001685646,0.0006106745],"category_scores_gemma":[0.0001986091,0.0002202998,0.00008508775,0.001465957,0.00006270954,0.0006590634,0.00008593562,0.0005022636,0.001033659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001846939,"about_ca_system_score_gemma":0.0000605396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009063514,"about_ca_topic_score_gemma":0.0000127209,"domain_scores_codex":[0.9984387,0.00004514771,0.0005564137,0.0002365379,0.0004001316,0.0003230551],"domain_scores_gemma":[0.9983001,0.00008067357,0.0005716179,0.0002454032,0.0007814087,0.00002080347],"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":[0.0001520703,0.0009753625,0.02344457,0.00066891,0.0002460934,0.00007681721,0.00009423901,0.5412099,0.0002834418,0.1872591,0.02115898,0.2244305],"study_design_scores_gemma":[0.0008622396,0.0001279284,0.007981311,0.0002233078,0.00007361987,0.00004874479,0.000109216,0.9738943,0.00007793416,0.008561737,0.007755082,0.000284587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0974476,0.00006723633,0.8606145,0.005493155,0.01013728,0.0009590943,0.00001128523,0.001535668,0.0237342],"genre_scores_gemma":[0.9737087,0.00001837491,0.01893823,0.004487977,0.002383659,0.00001370995,0.00005847416,0.00008874133,0.0003020819],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8762612,"threshold_uncertainty_score":0.9997442,"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."}}