{"id":"W2186951678","doi":"","title":"AN ANALYSIS OF THE ASSIGNMENT OF DELIVERY ROUTES TO VEHICLE DRIVERS IN STOCHASTIC VEHICLE ROUTING OPERATIONS","year":2004,"lang":"en","type":"article","venue":"","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Vehicle routing problem; Markov decision process; Operations research; Routing (electronic design automation); Markov chain; Markov process; Computer science; Range (aeronautics); Transport engineering; Engineering; Computer network","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":[0.004730858,0.0004017272,0.0004785536,0.001008478,0.0005148199,0.0009530953,0.0009053589,0.0006551529,0.002093666],"category_scores_gemma":[0.02135227,0.0005550338,0.0006535788,0.001131619,0.0009344438,0.001390314,0.0005958541,0.001012396,0.0001873237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002288144,"about_ca_system_score_gemma":0.0009966936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01219836,"about_ca_topic_score_gemma":0.01119302,"domain_scores_codex":[0.9975899,0.001123751,0.0000899656,0.0003329634,0.0004637363,0.0003995523],"domain_scores_gemma":[0.9743945,0.01998565,0.003040021,0.000884225,0.001233352,0.0004622651],"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":[0.0002365637,0.0001062369,0.02972987,0.0000297554,0.00006134184,0.0001298676,0.0003356084,0.9266823,0.001405596,0.0285809,0.0005289677,0.01217301],"study_design_scores_gemma":[0.00001143068,0.00008454439,0.01063966,0.000003702518,0.00001714856,0.00004545396,0.0001747097,0.9814752,0.0005253165,0.006674851,0.0003321687,0.00001571033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9074312,0.00008616279,0.09005819,0.0002474122,0.000009887448,0.00007644557,0.0001870663,0.00006121107,0.001842556],"genre_scores_gemma":[0.9908241,0.00006346699,0.00812177,0.00001632293,0.000007583074,0.00003477064,0.0001790871,0.00001701565,0.0007360135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01219836,"threshold_uncertainty_score":0.02501953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192264326474772,"score_gpt":0.2569814460373314,"score_spread":0.2450588027725836,"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."}}