{"id":"W7099114522","doi":"","title":"Bangladeshi Experience in Adapting Financial Services to Cope with Floods.” Study supported by USAID","year":2000,"lang":"en","type":"article","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microfinance; Financial services; State (computer science); Product (mathematics); Natural disaster; Unit (ring theory); Best practice; Corporation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002562085,0.000283221,0.0001767583,0.0005157074,0.004965486,0.002527762,0.0006184122,0.001026658,0.01254595],"category_scores_gemma":[0.00433375,0.000260564,0.0001674554,0.001384429,0.001526369,0.002076089,0.002522788,0.001557565,0.002625804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005366688,"about_ca_system_score_gemma":0.004986713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06515349,"about_ca_topic_score_gemma":0.16785,"domain_scores_codex":[0.9986768,0.0005381836,0.00004552252,0.00006174158,0.0001888525,0.0004889296],"domain_scores_gemma":[0.9984102,0.000273456,0.0002516383,0.00006409226,0.0002856879,0.0007149302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003217493,0.0009311217,0.1583662,0.0003592901,0.00004129714,0.003998769,0.5442393,0.0003187541,0.00154072,0.01027179,0.0965369,0.1830741],"study_design_scores_gemma":[0.00004174585,0.0003221736,0.1184753,0.0002115903,0.00001436963,0.0009896988,0.6438878,0.0001392349,0.0003272845,0.0004603534,0.2350864,0.00004407618],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8454181,0.001930962,0.0002107837,0.03223674,0.0002027704,0.0001793485,0.0008376852,0.00003269725,0.1189509],"genre_scores_gemma":[0.9695152,0.003073371,0.000258762,0.003209004,0.00003840689,0.00008447345,0.000278125,0.00002140015,0.02352124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06515349,"threshold_uncertainty_score":0.1295485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01149734760936521,"score_gpt":0.2323011813543625,"score_spread":0.2208038337449972,"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."}}