{"id":"W2609748945","doi":"10.1051/ro/2017030","title":"Impact of vehicle tracking on a routing problem with dynamic travel times","year":2017,"lang":"en","type":"article","venue":"RAIRO - Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Schedule; Computer science; Vehicle routing problem; Routing (electronic design automation); Adaptive routing; Dynamic positioning; Operations research; Real-time computing; Transport engineering; Static routing; Engineering; Computer network; Routing protocol; Marine 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":[0.001290852,0.0001494339,0.0002106116,0.0002524795,0.0008677082,0.0003664612,0.0004038394,0.00008664918,0.0001040624],"category_scores_gemma":[0.0004177833,0.0001231917,0.00006549838,0.0002846752,0.0001656092,0.0003792529,0.00005716143,0.0004732735,0.00002888526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002230897,"about_ca_system_score_gemma":0.0001611499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002494701,"about_ca_topic_score_gemma":0.0001381515,"domain_scores_codex":[0.9984286,0.0001801172,0.0002680592,0.0002351656,0.0004596879,0.0004283139],"domain_scores_gemma":[0.9986718,0.0001766845,0.00003116487,0.0006735142,0.0003484795,0.00009837029],"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":[0.0000217933,0.00006155807,0.003008992,0.00003330176,0.00006286658,0.00000325257,0.00084503,0.9581773,0.02715793,0.0007077107,0.00004670088,0.009873563],"study_design_scores_gemma":[0.0005099913,0.0002377371,0.07322787,0.0001327084,0.000006245944,0.00000449194,0.0001117828,0.9188042,0.006789393,0.00002832443,0.00000503771,0.0001422678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9333844,0.0000261543,0.05322124,0.000213419,0.00002981576,0.0005453875,0.00002405376,0.0001238671,0.0124317],"genre_scores_gemma":[0.9646874,0.00001493995,0.03444955,0.000002291441,0.00003563009,0.00004326779,0.00001085651,0.00005904157,0.0006970044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07021888,"threshold_uncertainty_score":0.6673798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06383388641025729,"score_gpt":0.4121994141531776,"score_spread":0.3483655277429203,"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."}}