{"id":"W4376127174","doi":"10.1016/j.tele.2023.101995","title":"Behind the growth of FinTech in South Korea: Digital divide in the use of digital financial services","year":2023,"lang":"en","type":"article","venue":"Telematics and Informatics","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Financial services; FinTech; Business; The Internet; Digital divide; Index (typography); Marketing; Finance; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004354782,0.0001292133,0.0001331993,0.00120234,0.001198297,0.003149458,0.0003775294,0.0007335246,0.009939092],"category_scores_gemma":[0.0009553996,0.0001316197,0.000190527,0.001995287,0.0009306357,0.002889386,0.002079292,0.001892237,0.0005841859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002983569,"about_ca_system_score_gemma":0.004569501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04199725,"about_ca_topic_score_gemma":0.08586139,"domain_scores_codex":[0.9995951,0.00002889478,0.00002082678,0.00004912533,0.00005388061,0.0002521376],"domain_scores_gemma":[0.9984842,0.0001469039,0.000459598,0.00002538989,0.0001645961,0.0007193604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003315798,0.000293207,0.8525686,0.0001794223,0.00004313114,0.001861393,0.01801125,0.0006039243,0.002377474,0.06428812,0.01109858,0.04834332],"study_design_scores_gemma":[0.00001699516,0.00007086399,0.8966852,0.0001382125,0.0000240273,0.0002699645,0.07660518,0.0009675064,0.0007145306,0.003139267,0.02133333,0.00003481678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872407,0.0002319267,0.00004738775,0.004998053,0.0000150204,0.000009577505,0.0003167608,0.00000557005,0.007134989],"genre_scores_gemma":[0.9975448,0.0001306857,0.00002377452,0.000346799,0.000006128343,0.000002742333,0.00007422588,0.00000234371,0.001868464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04199725,"threshold_uncertainty_score":0.08350563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02843491432740544,"score_gpt":0.2091006838368085,"score_spread":0.1806657695094031,"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."}}