{"id":"W2952654711","doi":"10.5430/ijfr.v10n5p280","title":"Measuring the Outreach Level of Micro-finance Institutions in Bangladesh","year":2019,"lang":"en","type":"article","venue":"International Journal of Financial Research","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outreach; Microfinance; Business; Loan; Collateral; Financial system; Economic growth; Finance; Actuarial science; Economics; Demographic economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003481268,0.0001157415,0.0003920614,0.0009033093,0.000099805,0.00005209947,0.001253835,0.0001307599,0.0001117839],"category_scores_gemma":[0.001040593,0.0001035126,0.0001935354,0.0006652295,0.0001852474,0.0003912887,0.0002649639,0.0007735829,0.0002261083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003709277,"about_ca_system_score_gemma":0.0004796903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008417424,"about_ca_topic_score_gemma":0.000241836,"domain_scores_codex":[0.9978974,0.00005500327,0.001132079,0.0002223951,0.0003574137,0.0003356471],"domain_scores_gemma":[0.9981871,0.0001690957,0.0006048842,0.0002541983,0.0007477507,0.00003699103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004954828,0.0005801407,0.2753899,0.00004300728,0.00005163857,0.0001150439,0.002450824,0.0006594589,0.01373057,0.6721746,0.003197365,0.03111196],"study_design_scores_gemma":[0.001892893,0.0002502964,0.7452873,0.0004766567,0.00000276351,0.0000605451,0.00009544966,0.0001151894,0.009239342,0.02880534,0.2135465,0.0002276836],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835094,0.003185204,0.001143559,0.001761784,0.001499208,0.0002121416,0.0001225228,0.000002463933,0.008563687],"genre_scores_gemma":[0.9968542,0.001301155,0.0004987105,0.00009558776,0.0003225245,0.000006550727,0.000003326164,0.00001248778,0.0009054077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6433693,"threshold_uncertainty_score":0.4221121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3211756797814806,"score_gpt":0.3767805061772714,"score_spread":0.05560482639579084,"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."}}