{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001947934,0.0003401996,0.0004228271,0.0001944983,0.0002600127,0.00006601779,0.0002765385,0.0003481173,0.00009058076],"category_scores_gemma":[0.00004256074,0.0004005808,0.00009074643,0.00004760813,0.00007995188,0.0001867025,0.000120528,0.0002977054,0.00001662587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006317969,"about_ca_system_score_gemma":0.00004924072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006154517,"about_ca_topic_score_gemma":0.00000352886,"domain_scores_codex":[0.9986207,0.00001235628,0.0005622242,0.0003842864,0.0002114596,0.0002088963],"domain_scores_gemma":[0.9985279,0.00008499938,0.000390992,0.0005821876,0.0002913602,0.0001225205],"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":[0.000002449331,0.000007150481,0.000004673977,0.0001043933,0.00006035031,1.35889e-7,0.0001818885,0.9220439,0.000317504,0.07287822,0.00002781413,0.004371515],"study_design_scores_gemma":[0.000242838,0.000007769933,0.000006856267,0.00009336245,0.00009031101,0.00000104815,0.000007239281,0.9940467,0.0003361012,0.001817207,0.002989437,0.0003611084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003829412,0.00035208,0.8003324,0.000065358,0.00004418956,0.0007566217,0.0001222676,0.0003282582,0.1979605],"genre_scores_gemma":[0.1242242,0.004443552,0.5328627,0.0001591599,0.0005069102,0.000427773,0.0005069515,0.00081987,0.3360489],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2674697,"threshold_uncertainty_score":0.9998446,"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."}}