{"id":"W4387454750","doi":"10.3390/risks11100175","title":"Microinsurance and Economic Growth in Africa","year":2023,"lang":"en","type":"article","venue":"Risks","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Microinsurance; Economics; Nexus (standard); Development economics; Poverty; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009268487,0.00006501091,0.00008282661,0.000008474144,0.00007661201,0.0000233636,0.0001017633,0.00004373504,0.00003382088],"category_scores_gemma":[0.00001261624,0.00001979464,0.00002266864,0.0002202365,0.00003667273,0.00006693279,0.0000472717,0.00006133383,0.0002451215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000123026,"about_ca_system_score_gemma":0.000002028828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001179458,"about_ca_topic_score_gemma":0.0008545626,"domain_scores_codex":[0.9994676,0.0000201506,0.00008987158,0.0001771512,0.00004409105,0.0002011362],"domain_scores_gemma":[0.9998237,0.00008483623,0.00002309452,0.00001599344,0.000006666019,0.00004567684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001656209,0.00002314937,0.8409874,0.000007040672,0.000003707331,0.00002093605,0.0002982779,0.00004376024,0.0886931,0.0005466039,0.006722764,0.06263664],"study_design_scores_gemma":[0.00005059872,0.0000265529,0.9926668,0.000006912595,8.550446e-7,0.000003350542,0.0001689022,0.00007908176,0.000993814,0.0005162896,0.005405906,0.00008090412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973218,0.0002984271,6.661104e-8,0.0009307856,0.00005148923,0.00006840679,0.00001297728,0.00005544577,0.001260598],"genre_scores_gemma":[0.9982839,0.001074424,0.00001001116,0.00002152803,0.00006960917,0.000006442314,0.00000656062,2.714785e-7,0.0005272872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1516794,"threshold_uncertainty_score":0.3150623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0339129592626693,"score_gpt":0.2359882357856747,"score_spread":0.2020752765230054,"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."}}