{"id":"W2782124575","doi":"10.1007/978-3-319-69215-9_3","title":"Cumulative VRP: A Simplified Model of Green Vehicle Routing","year":2017,"lang":"en","type":"book-chapter","venue":"Springer optimization and its applications","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Vehicle routing problem; Context (archaeology); Mathematical optimization; Column generation; Cumulative distribution function; Routing (electronic design automation); Integer programming; Computer science; Mathematics; Statistics; Geography; Probability density function","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":[0.0003605651,0.0008724524,0.001058492,0.000687451,0.0004352603,0.002047391,0.002551725,0.001519638,0.00913247],"category_scores_gemma":[0.001462176,0.0005521594,0.0009352731,0.001826542,0.0009002404,0.001992908,0.001094208,0.001547359,0.001791836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001592772,"about_ca_system_score_gemma":0.001264163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01123343,"about_ca_topic_score_gemma":0.00870361,"domain_scores_codex":[0.9996856,0.00009036507,0.00001031658,0.00005566444,0.0001094353,0.000048603],"domain_scores_gemma":[0.9997761,0.00008458341,0.00002636281,0.00003428827,0.00005423756,0.00002452141],"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":[0.00001352067,0.000009603128,0.00006533124,0.00003980105,0.00001050167,0.00004217273,0.00001930201,0.7982947,0.0004493108,0.1859769,0.003787531,0.01129126],"study_design_scores_gemma":[0.000003522883,0.000005991906,0.00004867245,0.000006944551,0.000005049027,0.00002270815,0.000006073591,0.9193771,0.0000829512,0.07605943,0.004374675,0.000006906851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0112104,0.001733212,0.940049,0.0007443951,0.0003601576,0.00004922392,0.0007651699,0.0003276187,0.04476081],"genre_scores_gemma":[0.6767352,0.005944783,0.181247,0.0005545677,0.0005468631,0.000313845,0.001338478,0.0007970881,0.1325222],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01123343,"threshold_uncertainty_score":0.0305512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04099849479783745,"score_gpt":0.2771836858224028,"score_spread":0.2361851910245653,"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."}}