{"id":"W3034784053","doi":"10.3390/jrfm13060122","title":"Microfinance Participation in Thailand","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microfinance; Loan; Multinomial logistic regression; Household income; Business; Socioeconomic status; Demographic economics; Inequality; Survey data collection; Dependency ratio; Financial services; Economics; Labour economics; Socioeconomics; Economic growth; Finance; Geography; Population","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":[0.0005239809,0.0001496016,0.0001264525,0.0007296313,0.0006934504,0.001173947,0.0002663036,0.0001780011,0.007538453],"category_scores_gemma":[0.001656367,0.00009605559,0.000206133,0.001642352,0.000356026,0.0006330002,0.000978991,0.000383322,0.0003015412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008542858,"about_ca_system_score_gemma":0.001453453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03818179,"about_ca_topic_score_gemma":0.03699156,"domain_scores_codex":[0.9993141,0.0001853895,0.00005824695,0.00007275219,0.0001595088,0.0002099991],"domain_scores_gemma":[0.9977216,0.0004182412,0.00103219,0.0000496351,0.0002171622,0.0005611511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008941176,0.0001942064,0.9259977,0.000245946,0.00004887283,0.00146184,0.005883485,0.001121859,0.000271051,0.002547178,0.003224997,0.05891348],"study_design_scores_gemma":[0.000008331662,0.0001081904,0.9753283,0.0001689853,0.00002151777,0.0006606756,0.0136994,0.002314065,0.0001332096,0.000610893,0.006926961,0.00001945285],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883134,0.0005288685,0.0002521254,0.0005197172,0.00001072132,0.00002911391,0.0008922154,0.0000107897,0.009443007],"genre_scores_gemma":[0.9980091,0.0002924223,0.00007325639,0.00002852959,0.000004723416,0.00001729549,0.0002458929,0.000002042973,0.00132661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03818179,"threshold_uncertainty_score":0.07591909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01930313308333639,"score_gpt":0.222179429180014,"score_spread":0.2028762960966776,"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."}}