{"id":"W6902032514","doi":"10.6084/m9.figshare.14433458","title":"Additional file of Socio-economic and demographic determinants of female genital mutilation in sub-Saharan Africa: analysis of data from demographic and health surveys","year":2021,"lang":"en","type":"article","venue":"Open MIND","topic":"Female Genital Mutilation/Cutting Issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Female circumcision; Population; Public health; Epidemiology; Reproductive health; Health data; Demographic analysis; Population health","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006748719,0.0001212159,0.0007015327,0.0004404847,0.00003948013,0.00001796726,0.0001608501,0.00008700422,0.05654451],"category_scores_gemma":[0.0002504696,0.0001307666,0.00007093489,0.0007111544,0.000191397,0.0002633056,0.0002498641,0.00008388787,0.000005192833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000204166,"about_ca_system_score_gemma":0.0002689849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005216394,"about_ca_topic_score_gemma":0.007234262,"domain_scores_codex":[0.9984053,0.0001924304,0.0006638583,0.0004300646,0.0001625981,0.0001457588],"domain_scores_gemma":[0.9980676,0.0008934188,0.0004375011,0.0004234257,0.00009545357,0.00008257984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006237776,0.000184474,0.960335,0.00007772102,0.0005258746,0.00001279249,0.0005862013,0.0000084932,0.000646718,4.641772e-7,0.005083688,0.03247618],"study_design_scores_gemma":[0.0005758332,0.00008938249,0.9927365,0.0002500415,0.0003347744,0.000006404887,0.0003989598,0.004298554,0.0006617291,0.00002548539,0.0005277262,0.00009462883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7713344,0.0009357096,0.000006476469,0.00003005348,0.000009421497,0.0002020368,0.2273529,7.921651e-7,0.0001282723],"genre_scores_gemma":[0.9193226,0.0001294848,0.008349242,0.000004967093,0.00001373218,0.00001180616,0.07210324,0.00001016496,0.00005473683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1552496,"threshold_uncertainty_score":0.9443179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032022637752529,"score_gpt":0.3463237650822208,"score_spread":0.243121501306968,"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."}}