{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005279286,0.0008361098,0.0006239072,0.0006099127,0.0002740086,0.0007844013,0.00062822,0.000799004,0.001286092],"category_scores_gemma":[0.0009833131,0.0003690464,0.0006094778,0.0006268235,0.0003154192,0.0007305733,0.0004590652,0.0003936836,0.0001220728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007934648,"about_ca_system_score_gemma":0.0009727784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00575738,"about_ca_topic_score_gemma":0.00657812,"domain_scores_codex":[0.9997893,0.00007251304,0.000006273701,0.00004004753,0.00003697545,0.00005485178],"domain_scores_gemma":[0.9997739,0.0001137442,0.00004292738,0.00001315102,0.00002984267,0.0000264618],"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":[0.00002804186,0.00002886335,0.0003166256,0.00002511238,0.00001215809,0.00002455062,0.000004290191,0.9935401,0.000945516,0.0007786323,0.00009981079,0.004196323],"study_design_scores_gemma":[0.000007157172,0.00004418012,0.0002159506,0.000003550701,0.000008855384,0.00001113273,0.00001581933,0.9981672,0.0006294288,0.0006486076,0.0002456274,0.000002548041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6955446,0.0008333287,0.2887422,0.0002978153,0.00006507519,0.0001520671,0.0003293342,0.0001757717,0.01385983],"genre_scores_gemma":[0.9448363,0.0002228026,0.0516585,0.00002848673,0.000007876679,0.00008522315,0.0001563791,0.00003494344,0.002969464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00575738,"threshold_uncertainty_score":0.01144779,"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."}}