{"id":"W3175587957","doi":"10.3390/su13126940","title":"Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Benchmark (surveying); Vehicle routing problem; Metaheuristic; Ant colony optimization algorithms; Computer science; Mathematical optimization; Variable (mathematics); Composition (language); Routing (electronic design automation); Operations research; Engineering; Algorithm; Mathematics; Embedded system","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":[0.0002963493,0.00008944637,0.0001430501,0.00004680171,0.00004696324,0.00001400466,0.0000379005,0.00008467513,0.00003335101],"category_scores_gemma":[0.0001372403,0.0001020938,0.000033627,0.0002077255,0.00006747443,0.00007992864,0.00003992772,0.00008763849,8.497129e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229381,"about_ca_system_score_gemma":0.0001006774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003880117,"about_ca_topic_score_gemma":0.000001921068,"domain_scores_codex":[0.9991909,0.0001525979,0.0002350608,0.000164096,0.0001320171,0.0001252927],"domain_scores_gemma":[0.9990929,0.00008561663,0.00003985094,0.0001658687,0.0005623451,0.00005342263],"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":[0.00001126872,0.00003762911,0.01637463,0.000450284,0.00001730918,0.000002427365,0.0001635903,0.9760787,0.004414337,0.0007769721,0.00001113643,0.001661642],"study_design_scores_gemma":[0.0003879855,0.00001502233,0.02142568,0.00002616286,0.000021786,0.000007396487,0.0003702097,0.9561519,0.01669536,0.004745497,0.00002782812,0.0001251583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8052436,0.00024709,0.1933769,0.0004648323,0.0000703903,0.0001443044,0.000005878839,0.000119351,0.0003277178],"genre_scores_gemma":[0.9767855,0.0000170573,0.02300552,0.00001244664,0.00002111603,0.00000549006,0.00004040208,0.0000153335,0.00009717034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1715419,"threshold_uncertainty_score":0.4163266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00933232368733773,"score_gpt":0.2598773016191051,"score_spread":0.2505449779317673,"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."}}