{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006684029,0.00009008833,0.0001516086,0.0003770051,0.0000993545,0.00003737019,0.00003976201,0.00003168351,0.00003400957],"category_scores_gemma":[0.00004697386,0.00009395393,0.00002156941,0.0005737076,0.00002480855,0.0002088185,0.00003485422,0.00006743841,0.000004543143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000340832,"about_ca_system_score_gemma":0.000002904745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000493853,"about_ca_topic_score_gemma":0.000008259308,"domain_scores_codex":[0.9992661,0.00006437345,0.0002490579,0.0001590794,0.0001193219,0.0001420249],"domain_scores_gemma":[0.9997351,0.00001646448,0.00002301905,0.0001432331,0.00002703157,0.00005515408],"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":[0.000004170464,0.0001023345,0.0277724,0.00006317472,0.0003093161,3.63891e-7,0.001561382,0.909518,0.04300512,0.0006666828,0.000131054,0.01686601],"study_design_scores_gemma":[0.0002302961,0.000009501712,0.1156586,0.00003111316,0.0003532629,0.000002038722,0.0006143521,0.8308186,0.05202026,0.000007790926,0.00007150539,0.0001826764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631579,0.0002182277,0.03437366,0.0002101662,0.00009775695,0.0002961723,0.000004798638,0.00007659285,0.001564729],"genre_scores_gemma":[0.9913799,0.0002945266,0.007860703,0.00001510724,0.00003244449,0.00002322879,0.00001715627,0.00001186908,0.0003651229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08788622,"threshold_uncertainty_score":0.383133,"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."}}