{"id":"W4406322241","doi":"10.1109/3ict64318.2024.10824667","title":"Determining Delivery Demand Area Distribution Using Effective Regions of Movement Clustering","year":2024,"lang":"en","type":"article","venue":"","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of the Fraser Valley","funders":"","keywords":"Cluster analysis; Computer science; Movement (music); Distribution (mathematics); Artificial intelligence; Mathematics","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":[0.0005709784,0.0005061552,0.0004121397,0.004317147,0.0003374012,0.0008221584,0.0008345195,0.0004388652,0.001056145],"category_scores_gemma":[0.002894319,0.0001830511,0.0005397044,0.003172633,0.0002564369,0.0005594994,0.0006450942,0.0002884029,0.0006640077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000761635,"about_ca_system_score_gemma":0.0005403741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02249502,"about_ca_topic_score_gemma":0.02272598,"domain_scores_codex":[0.999382,0.0001158198,0.00004474732,0.0002126461,0.0001342052,0.0001106071],"domain_scores_gemma":[0.9988146,0.0004023598,0.0002086303,0.0001556456,0.000350211,0.00006861131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000742248,0.0003139094,0.4740072,0.0003320709,0.0003612042,0.00061647,0.0007321698,0.3537141,0.009353362,0.006783363,0.01586093,0.137183],"study_design_scores_gemma":[0.00002231553,0.00006962232,0.1212483,0.00002873649,0.0000570039,0.0003672887,0.0008915736,0.8648475,0.003222762,0.002218472,0.006987112,0.00003930755],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8973243,0.0007301726,0.08340337,0.0002380623,0.00003039964,0.0001647739,0.0120186,0.0009467961,0.005143463],"genre_scores_gemma":[0.9697911,0.0001444246,0.02054041,0.00001802865,0.00001449494,0.00006000817,0.008410725,0.00005516193,0.0009656753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02249502,"threshold_uncertainty_score":0.04472822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730660532658773,"score_gpt":0.2139603828010212,"score_spread":0.1866537774744335,"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."}}