{"id":"W4205158948","doi":"10.2139/ssrn.4012376","title":"Machine Learning for Data-Driven Last-Mile Delivery Optimization","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Mile; Last mile (transportation); Computer science; Geography","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":[0.002829305,0.001392448,0.002718973,0.001197459,0.0007698869,0.001683257,0.002246991,0.002375018,0.004973755],"category_scores_gemma":[0.009109654,0.00126406,0.001303941,0.001304662,0.001008896,0.001553184,0.001811877,0.003231531,0.0009223819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001738637,"about_ca_system_score_gemma":0.002535964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01173561,"about_ca_topic_score_gemma":0.006973781,"domain_scores_codex":[0.9991577,0.0003222614,0.00004731299,0.0001727845,0.0001619119,0.0001381682],"domain_scores_gemma":[0.9953638,0.00349929,0.000234656,0.0002078825,0.0005455373,0.0001487213],"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":[0.00003336606,0.00003017378,0.0001974949,0.00003003958,0.00001498429,0.00001301828,0.000006348705,0.9883258,0.00008758928,0.001395375,0.000638616,0.009227282],"study_design_scores_gemma":[0.000001818051,0.000003496543,0.00001556581,0.000001505417,7.644398e-7,9.193904e-7,8.865704e-7,0.9990795,0.00003035772,0.0008121485,0.0000521828,8.540355e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02494135,0.0007687333,0.9693205,0.0007327158,0.0001325965,0.00009744699,0.0004605562,0.0009658345,0.002580344],"genre_scores_gemma":[0.817951,0.0004690223,0.1711334,0.0003644482,0.0002183391,0.0004861034,0.001742348,0.0003628948,0.007272613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01173561,"threshold_uncertainty_score":0.02333462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194308073570458,"score_gpt":0.2217091643494694,"score_spread":0.2097660836137648,"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."}}