{"id":"W4380050538","doi":"10.3390/jrfm16060296","title":"Developing a Multidimensional Financial Inclusion Index: A Comparison Based on Income Groups","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Financial inclusion; Index (typography); Economics; Financial literacy; Financial sector development; Poverty; Econometrics; Order (exchange); Finance; Actuarial science; Financial sector; Financial services; Economic growth; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002593883,0.0004815388,0.0004976658,0.01022003,0.0004815719,0.001802793,0.0004102228,0.000400761,0.002166139],"category_scores_gemma":[0.007153565,0.00009117687,0.0007190933,0.008571283,0.000485919,0.002537551,0.001784155,0.0003891059,0.0004338843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004898403,"about_ca_system_score_gemma":0.000588854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001167604,"about_ca_topic_score_gemma":0.001097249,"domain_scores_codex":[0.9982423,0.0007365058,0.0002051879,0.0001535361,0.0005066063,0.0001560107],"domain_scores_gemma":[0.9968437,0.00101577,0.0008768145,0.0002211128,0.0007830387,0.0002596074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002769549,0.0002723347,0.850479,0.0001997136,0.0002634772,0.0001291427,0.00124118,0.001796679,0.0007964249,0.004390203,0.001665917,0.1384889],"study_design_scores_gemma":[0.00003019854,0.0006007429,0.9644273,0.0002093621,0.000150232,0.0002862476,0.006316573,0.0118403,0.001885109,0.005016373,0.009175431,0.0000620529],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706956,0.0005857069,0.01434839,0.0003195108,0.00004745989,0.0002185271,0.001460548,0.00004351992,0.01228069],"genre_scores_gemma":[0.9821237,0.0002823138,0.01464032,0.00003806318,0.00003174649,0.0002335135,0.00217931,0.00001153379,0.0004596104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01022003,"threshold_uncertainty_score":0.01371795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02153044132083472,"score_gpt":0.2418720097489928,"score_spread":0.2203415684281581,"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."}}