{"id":"W2073441261","doi":"10.1080/20932685.2011.10593078","title":"Profiling Chinese Fashion Shoppers in Beijing: Mall Activities, Shopping Outcome, and Demographics","year":2011,"lang":"en","type":"article","venue":"Journal of Global Fashion Marketing","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Beijing; Profiling (computer programming); Demographics; Shopping mall; Business; Advertising; China; Marketing; Computer science; Geography; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002421237,0.0003077573,0.0005041275,0.0004242432,0.0002050062,0.0002023652,0.0002760564,0.000114123,0.00003440871],"category_scores_gemma":[0.0009484283,0.0002676781,0.0001881221,0.000822017,0.0000907638,0.00174965,0.0003357718,0.0004487613,0.000002964847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000136823,"about_ca_system_score_gemma":0.00003280396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001825661,"about_ca_topic_score_gemma":0.0004813897,"domain_scores_codex":[0.9978704,0.00008214833,0.0009082271,0.0002707032,0.0004381436,0.0004303691],"domain_scores_gemma":[0.9986281,0.0001459931,0.0008508519,0.0001435043,0.0001926798,0.00003887427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002743804,0.00006795712,0.9876924,0.00016762,0.00004677144,0.00009895018,0.000005239489,0.000002111369,0.0002672614,0.0005561828,0.00001465423,0.01080647],"study_design_scores_gemma":[0.0008003214,0.00001865813,0.9955738,0.000215911,0.0001118811,0.00005958479,0.002528617,0.0002273698,3.457974e-8,0.00000108059,0.0001890424,0.0002737225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938695,0.0003266713,0.0001055819,0.0002894096,0.0005548678,0.0001892051,0.000001533653,0.00004389521,0.004619318],"genre_scores_gemma":[0.998274,0.00009286148,0.001227098,0.000177876,0.0001863645,0.000003738515,0.000001389034,0.00002410586,0.00001253991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01053275,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0366227281419235,"score_gpt":0.2693443117920343,"score_spread":0.2327215836501108,"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."}}