{"id":"W4379390809","doi":"10.32920/23296070","title":"Shopping Centre Classifications: A Dynamic Approach","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Metropolitan area; Hierarchy; Analytics; Computer science; Multivariate statistics; Business; Data science; Geography; Machine learning; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002613921,0.0003841453,0.0004028915,0.0005033316,0.0002367193,0.0006320444,0.0005752729,0.0001626172,0.0002139866],"category_scores_gemma":[0.0001150131,0.0003682958,0.000222999,0.000462795,0.00007942982,0.0002467305,0.002725112,0.0005091605,0.002236968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000101672,"about_ca_system_score_gemma":0.00003999104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000685205,"about_ca_topic_score_gemma":0.00133601,"domain_scores_codex":[0.9980436,0.00001002488,0.0004222148,0.0008068935,0.0003326719,0.0003846253],"domain_scores_gemma":[0.9986707,0.00003699129,0.000290868,0.0007764444,0.0002142839,0.00001072721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001745366,0.0004499107,0.846437,0.003945576,0.0006792733,0.00004646766,0.0001856962,0.0002083332,0.0001138115,0.03768902,0.02365481,0.08657261],"study_design_scores_gemma":[0.0008977399,0.000002266152,0.6310731,0.0008503249,0.001878544,0.000003771342,0.007372257,0.21635,0.000001327609,0.004629982,0.1338343,0.00310636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.317938,0.003432975,0.0269959,0.04343012,0.01138043,0.008537847,0.0001284171,0.01661577,0.5715405],"genre_scores_gemma":[0.9577314,0.0001726147,0.002798608,0.0003236216,0.0004397331,0.0005913354,0.001152566,0.0002221096,0.03656803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6397934,"threshold_uncertainty_score":0.9998769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1033237682343444,"score_gpt":0.2856103059214971,"score_spread":0.1822865376871527,"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."}}