{"id":"W4311938451","doi":"10.32920/21690440.v1","title":"Using data mining to analyze fashion consumers’ preferences from a cross-national perspective","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Fashion and Cultural Textiles","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Toronto Metropolitan University","funders":"","keywords":"Clothing; Preference; Advertising; Fashion design; Innovator; Perspective (graphical); Marketing; Style (visual arts); Order (exchange); Business; Set (abstract data type); Psychology; Computer science; Geography; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002808554,0.0003325735,0.0004623941,0.003873067,0.0004805883,0.001737145,0.0003515276,0.000414833,0.001039149],"category_scores_gemma":[0.007927753,0.0001740486,0.0007919193,0.005152156,0.0002669119,0.001314619,0.0006193786,0.0005461206,0.0003028691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005101247,"about_ca_system_score_gemma":0.0005525872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005306859,"about_ca_topic_score_gemma":0.007229919,"domain_scores_codex":[0.9982936,0.0007951885,0.0002065498,0.0003105038,0.0002925586,0.0001015979],"domain_scores_gemma":[0.9920967,0.00513421,0.001025432,0.0006852729,0.0008769397,0.000181543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003096413,0.0007400065,0.8623798,0.0002656425,0.0005338221,0.000369742,0.003328226,0.005144117,0.005032767,0.001850624,0.001267664,0.1187779],"study_design_scores_gemma":[0.00004408244,0.0005490066,0.855123,0.0001619827,0.0002652937,0.0005773673,0.01942181,0.1057923,0.005535199,0.005939282,0.006509354,0.00008131968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771484,0.0001439314,0.01742183,0.0004129198,0.00001443806,0.0001206297,0.001851856,0.0000661169,0.002819879],"genre_scores_gemma":[0.9689023,0.0001219446,0.02823649,0.00007010104,0.00001331075,0.0001204153,0.002161766,0.000009730648,0.0003639065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005306859,"threshold_uncertainty_score":0.01485324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3473905886957319,"score_gpt":0.3989408856767086,"score_spread":0.05155029698097668,"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."}}