{"id":"W3124640525","doi":"10.2139/ssrn.3171529","title":"Business Training for Microfinance Clients: How It Matters and for Whom?","year":2008,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Microfinance; Business; Training (meteorology); Economic growth; Economics; Geography","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":[0.007876501,0.0003143426,0.00107838,0.001566841,0.003841622,0.008990538,0.002045437,0.00585398,0.02942659],"category_scores_gemma":[0.04626587,0.0002656803,0.0005084942,0.002601053,0.003645088,0.00832282,0.004088858,0.006531565,0.002282231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006043748,"about_ca_system_score_gemma":0.01720453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05216944,"about_ca_topic_score_gemma":0.07720486,"domain_scores_codex":[0.9912389,0.003445511,0.0001825451,0.0003324592,0.0009086551,0.00389182],"domain_scores_gemma":[0.9494624,0.01561136,0.007116415,0.0006353395,0.004434938,0.02273964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006724176,0.004114605,0.3489581,0.000925787,0.000128491,0.0008040819,0.01720549,0.00042904,0.0002514184,0.03755467,0.1590067,0.4299492],"study_design_scores_gemma":[0.000442662,0.0008770907,0.6151016,0.008411559,0.0005529862,0.001162988,0.1898806,0.003675553,0.00124239,0.08654474,0.09185742,0.000250319],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2461898,0.007805937,0.0004701339,0.7151033,0.0007321895,0.00006299579,0.0004576719,0.00004040518,0.02913763],"genre_scores_gemma":[0.9735085,0.003529614,0.0002211699,0.01591463,0.0008147805,0.00006749877,0.0001182876,0.00003285147,0.005792754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05216944,"threshold_uncertainty_score":0.1037316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04561756163615897,"score_gpt":0.2375337909584001,"score_spread":0.1919162293222411,"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."}}