{"id":"W4396508724","doi":"10.1016/j.sste.2024.100655","title":"Analyzing the geographic influence of financial inclusion on illicit drug use in Nigeria","year":2024,"lang":"en","type":"article","venue":"Spatial and Spatio-temporal Epidemiology","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Financial inclusion; Illicit drug; Business; Geography; Traditional medicine; Drug; Socioeconomics; Medicine; Finance; Financial services; Economics; Pharmacology","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":[0.0005409843,0.0001690545,0.0001806599,0.001143994,0.0007358704,0.0007218297,0.0002164229,0.0001756906,0.001119924],"category_scores_gemma":[0.002191054,0.0001397848,0.0003124901,0.00176933,0.0004156568,0.0004353634,0.001029798,0.0002847953,0.0001090159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005480523,"about_ca_system_score_gemma":0.001034573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04408021,"about_ca_topic_score_gemma":0.09605929,"domain_scores_codex":[0.9996417,0.0001511592,0.0000392634,0.00003860785,0.00005348517,0.00007583376],"domain_scores_gemma":[0.9986823,0.0004432479,0.0005019355,0.00006647812,0.0001945062,0.0001114372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001945832,0.00001939561,0.9948426,0.0000190425,0.0000157857,0.0001416684,0.0009169144,0.0001463462,0.00008611935,0.0001324898,0.00008606072,0.003574138],"study_design_scores_gemma":[7.917304e-7,0.00003123971,0.9884766,0.00003793175,0.00002481329,0.0001479651,0.009962824,0.0006132898,0.0001004038,0.00008569092,0.0005142549,0.000004205163],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985865,0.000134607,0.0001101852,0.00007311341,0.000003807071,0.00001013306,0.0001736863,0.000001191988,0.0009067545],"genre_scores_gemma":[0.9993278,0.0001712839,0.000182228,0.000009093381,0.000003711624,0.000009725815,0.000129188,7.589248e-7,0.0001662693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04408021,"threshold_uncertainty_score":0.08764726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04016377290389746,"score_gpt":0.3378118308640209,"score_spread":0.2976480579601235,"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."}}