{"id":"W7128387139","doi":"10.5281/zenodo.18442647","title":"Last-Mile Logistics under E-commerce Growth: Efficiency and Emissions","year":2025,"lang":"en","type":"article","venue":"Open MIND","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Operational efficiency; Work (physics); Corporate governance; Consolidation (business); Customer service; Vehicle routing problem; Control (management); Supply chain; Framing (construction)","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":[0.001754518,0.0005535289,0.0005902174,0.0009162195,0.0003233831,0.003576671,0.0008051057,0.001152373,0.003448889],"category_scores_gemma":[0.002534216,0.0001515772,0.0007748935,0.002035848,0.001366123,0.003673333,0.0009422384,0.00111655,0.000411488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002406043,"about_ca_system_score_gemma":0.00200767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002716485,"about_ca_topic_score_gemma":0.002778571,"domain_scores_codex":[0.9992179,0.0002832919,0.00005940404,0.00009166574,0.0002313119,0.0001163745],"domain_scores_gemma":[0.9982429,0.000901029,0.0003289785,0.0000872876,0.0003809509,0.00005886527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000261182,0.0001610598,0.005162656,0.01338455,0.000455721,0.0003671836,0.0003387493,0.07399008,0.004499117,0.4200604,0.008182035,0.4731373],"study_design_scores_gemma":[0.0000575341,0.001015231,0.01502078,0.0205636,0.0007064788,0.001268089,0.002740769,0.03231671,0.021953,0.305379,0.5988166,0.0001621627],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09750033,0.6618825,0.03951167,0.01538408,0.000689448,0.0001361766,0.0004879212,0.0001186433,0.1842892],"genre_scores_gemma":[0.5751934,0.406957,0.008476952,0.001535417,0.000439299,0.0000972881,0.0002867742,0.00004197534,0.00697192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003576671,"threshold_uncertainty_score":0.01745719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04359820504839845,"score_gpt":0.2648926764182931,"score_spread":0.2212944713698947,"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."}}