{"id":"W7117348563","doi":"","title":"Mining Customer Journeys to Uncover Empirical Retail Agglomerations","year":2025,"lang":"en","type":"article","venue":"ScholarSpace (University of Hawaii at Manoa)","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urban agglomeration; Cluster analysis; Big data; Empirical research; Consumer behaviour; Cornerstone; Dimension (graph theory); Association rule learning; Interdependence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005661322,0.0004476848,0.0004869361,0.003805871,0.0006158905,0.0009703023,0.0007663644,0.0004501377,0.001486948],"category_scores_gemma":[0.004054449,0.0002780373,0.0007498826,0.005462729,0.0004233091,0.0011694,0.00107733,0.0006439317,0.000849238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008380645,"about_ca_system_score_gemma":0.0009403474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201696,"about_ca_topic_score_gemma":0.04947874,"domain_scores_codex":[0.999453,0.000156002,0.00004550328,0.0001633694,0.00008873884,0.00009330772],"domain_scores_gemma":[0.9978966,0.0007730714,0.0003546651,0.0004425863,0.0003813026,0.0001518812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003369084,0.0005022358,0.8011265,0.0004190575,0.0003495471,0.0006545007,0.003618457,0.05973619,0.002161527,0.008890605,0.01138575,0.1108188],"study_design_scores_gemma":[0.00003870288,0.0001687749,0.3806112,0.0001482797,0.00013259,0.0006134585,0.01339368,0.5584896,0.002686986,0.02067671,0.02296185,0.000078228],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549092,0.0003792818,0.03269404,0.0003815624,0.00002080872,0.00009569492,0.008209706,0.0003651911,0.002944377],"genre_scores_gemma":[0.9607571,0.0002335562,0.02744177,0.00003301972,0.00001064422,0.00007724317,0.01049302,0.00004823357,0.0009053256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201696,"threshold_uncertainty_score":0.04010439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03304279736169492,"score_gpt":0.2601072033301582,"score_spread":0.2270644059684633,"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."}}