{"id":"W4405036614","doi":"10.4236/ajor.2024.146009","title":"An Elementary Approach to the Vehicle Routing Problem via Python and Google API","year":2024,"lang":"en","type":"article","venue":"American Journal of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Python (programming language); Computer science; Vehicle routing problem; Programming language; World Wide Web; Information retrieval; Routing (electronic design automation); Computer network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003494664,0.00009237679,0.0001468239,0.0003103882,0.0003031603,0.0004483377,0.0002805819,0.00002063111,0.00002125438],"category_scores_gemma":[0.00007961147,0.00006756411,0.0000320702,0.001195932,0.0001183785,0.0003634345,0.00005545469,0.0005878104,0.00001153426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001140427,"about_ca_system_score_gemma":0.00009038626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001029184,"about_ca_topic_score_gemma":0.00001631416,"domain_scores_codex":[0.9982775,0.000514267,0.0003408199,0.0001510899,0.0004291979,0.0002871036],"domain_scores_gemma":[0.9991965,0.0001716921,0.00001595478,0.0002011136,0.0002441511,0.0001706403],"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":[0.000006683305,0.00003001236,0.0001929205,0.00001841816,0.00004831074,0.000004907759,0.003855389,0.8373274,0.01316436,0.0004232085,0.0005760243,0.1443524],"study_design_scores_gemma":[0.00008184001,0.0003136304,0.0003837463,0.00004051183,0.00001029907,0.00009475649,0.003211133,0.9930301,0.0009007724,0.00002649929,0.001817716,0.00008904115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4155295,0.0004349086,0.5803069,0.002077956,0.00009623494,0.0003171685,0.000005812386,0.00007993548,0.001151664],"genre_scores_gemma":[0.767467,0.00005934256,0.2321193,0.00004553191,0.0002043093,0.00001700694,0.000002663207,0.0000327374,0.00005212855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3519376,"threshold_uncertainty_score":0.4323331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03696489952496746,"score_gpt":0.370099402085067,"score_spread":0.3331345025600996,"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."}}