{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003934477,0.0001692473,0.0002862603,0.0003255208,0.0000578218,0.0007174875,0.0004355392,0.00006590511,0.000002735592],"category_scores_gemma":[0.0006475972,0.0001045385,0.00006119163,0.000936415,0.0001544188,0.00330452,0.0003849119,0.0001719701,0.00002668644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009600766,"about_ca_system_score_gemma":0.0000188051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006267733,"about_ca_topic_score_gemma":0.00007910014,"domain_scores_codex":[0.9984498,0.000003413459,0.0008815262,0.00007764123,0.0003314229,0.000256188],"domain_scores_gemma":[0.9988742,0.0002607406,0.000524035,0.0002378574,0.00009666759,0.000006510788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008190172,0.0003601695,0.7952881,0.01101953,0.00005031787,0.0000198978,0.04748673,0.0006557951,0.00001393268,0.1205457,0.004985244,0.01949259],"study_design_scores_gemma":[0.002889096,0.0002194965,0.5643356,0.003905314,0.0001190717,0.00002107394,0.03228962,0.2088794,0.0002100492,0.1652183,0.02047487,0.001438114],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957154,0.0000116907,0.0002751447,0.0001753213,0.00004607451,0.0003392501,0.00007090754,0.00002871277,0.003337486],"genre_scores_gemma":[0.9995077,0.00001138759,0.00009987605,0.0002294853,0.00004375172,0.00001115464,0.00004789259,0.00001203938,0.00003666995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2309525,"threshold_uncertainty_score":0.6918748,"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."}}