{"id":"W3208864393","doi":"10.32920/ryerson.14662236.v1","title":"Fashion trends: how political happenings influence consumers mindsets","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Fashion and Cultural Textiles","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Clothing; Style (visual arts); Politics; Consumption (sociology); Product (mathematics); Order (exchange); Identification (biology); Marketing; Advertising; Sociology; Political science; Business; Social science; Law; History","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007465249,0.0003843044,0.0004220472,0.0001248148,0.0002390938,0.001665292,0.0003386324,0.0002392487,0.01842337],"category_scores_gemma":[0.00006616161,0.0002968113,0.000295388,0.00003131886,0.0004713298,0.0002595668,0.0004122869,0.000617743,0.0002159105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006348991,"about_ca_system_score_gemma":0.00008720237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004253611,"about_ca_topic_score_gemma":0.003467961,"domain_scores_codex":[0.998241,0.00007210813,0.0002785584,0.0005649381,0.0003391684,0.0005042228],"domain_scores_gemma":[0.9989667,0.00005472209,0.0001227614,0.0003706871,0.0002506541,0.000234498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007036121,0.00008610513,0.0002274593,0.0001878215,0.0001531539,0.00006537233,0.04010121,0.000002746358,0.0001716136,0.9287579,0.02414825,0.006091301],"study_design_scores_gemma":[0.0008688848,0.0001111366,0.004952591,0.0007910686,0.0002766507,0.00004767186,0.3442567,0.0002205138,0.0006853408,0.001473489,0.6439722,0.002343806],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6650763,0.00006742892,0.000005232793,0.007029453,0.0008220308,0.0001054652,0.00007389885,0.000225575,0.3265946],"genre_scores_gemma":[0.8821511,0.00001965839,0.00009960651,0.001719064,0.0001980532,0.00002888525,0.0003335875,0.0000229184,0.1154271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9272844,"threshold_uncertainty_score":0.9999484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04394782638039505,"score_gpt":0.2556291302492856,"score_spread":0.2116813038688906,"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."}}