{"id":"W2126043710","doi":"10.1111/j.1937-5956.2012.01338.x","title":"Analysis of Travel Times and CO <sub>2</sub> Emissions in Time‐Dependent Vehicle Routing","year":2012,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":319,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Vehicle routing problem; Fuel efficiency; Greenhouse gas; Context (archaeology); Computer science; Scheduling (production processes); Limiting; Operations research; Environmental economics; Transport engineering; Routing (electronic design automation); Environmental science; Automotive engineering; Operations management; Economics; Engineering","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":[0.0007870641,0.0007357004,0.0003630034,0.0007447947,0.0002796473,0.000819004,0.0007895111,0.0007316529,0.001994291],"category_scores_gemma":[0.003281155,0.0004705427,0.0006793743,0.001101099,0.0004552575,0.0008684104,0.0002976288,0.0006584555,0.0001208017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002511638,"about_ca_system_score_gemma":0.0009415218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02077314,"about_ca_topic_score_gemma":0.01272479,"domain_scores_codex":[0.9995647,0.0001566702,0.00001427008,0.0000707181,0.00009069531,0.0001029702],"domain_scores_gemma":[0.9975823,0.001680773,0.000339857,0.00008464803,0.0002301382,0.00008222902],"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":[0.00003081501,0.00001263947,0.0005122446,0.00001382654,0.0000131079,0.00001795929,0.000009531334,0.9945681,0.0007068545,0.002751865,0.0001182463,0.001244784],"study_design_scores_gemma":[0.00000178889,0.000008632847,0.0004510756,0.000001446732,0.000005173757,0.00000803204,0.00001210932,0.9982829,0.0002737893,0.0008418148,0.0001100354,0.000003197385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8195189,0.0005695216,0.170147,0.0005134571,0.00004403132,0.0000714123,0.0007024629,0.0002197188,0.008213497],"genre_scores_gemma":[0.9854503,0.0002008507,0.01154556,0.00002772759,0.00000627785,0.00003178265,0.0002565884,0.00004988477,0.002431177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02077314,"threshold_uncertainty_score":0.04130447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01247377138778854,"score_gpt":0.2547284891803219,"score_spread":0.2422547177925333,"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."}}