{"id":"W2902727815","doi":"10.1111/sifp.12078","title":"Using Marketing Science to Understand Contraceptive Demand in High‐Fertility Niger","year":2018,"lang":"en","type":"article","venue":"Studies in Family Planning","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"United States Agency for International Development; United Nations Population Fund; Bill and Melinda Gates Foundation; William and Flora Hewlett Foundation; Physicians' Services Incorporated Foundation; World Bank Group","keywords":"Fertility; Psychological intervention; Latent class model; Family planning; Marketing; Population; Business; Medicine; Psychology; Environmental health; Computer science; Research methodology; Nursing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001421981,0.0001239394,0.0003283445,0.0001882303,0.0002238329,0.0000135997,0.00008531573,0.00003578431,0.000003479783],"category_scores_gemma":[0.0005083079,0.0001016542,0.00001638782,0.0005130538,0.0004778124,0.0001060421,0.0001532354,0.0001636503,0.000006869976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005185049,"about_ca_system_score_gemma":0.00008259192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004350223,"about_ca_topic_score_gemma":0.0001056165,"domain_scores_codex":[0.9985838,0.00006439582,0.0002862858,0.0003266229,0.0002660352,0.0004728753],"domain_scores_gemma":[0.9994565,0.0001274011,0.00004834519,0.0001221895,0.000143645,0.0001019598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008784442,0.00003501267,0.9822019,0.000110491,0.00001823577,0.000111119,0.01346361,0.00004398747,0.00257628,0.00006007875,0.0001252969,0.0003755118],"study_design_scores_gemma":[0.0007773438,0.0001398059,0.9682568,0.00172902,0.000009148454,0.000006921724,0.02835712,0.0001962282,0.0001239696,0.0002647692,0.00004045679,0.00009836451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994107,0.001294679,0.00007535092,0.0002528876,0.0003923518,0.0003411469,0.000003280094,0.00001957253,0.003513711],"genre_scores_gemma":[0.9962084,0.00003316331,0.001453888,0.00213482,0.0001418543,0.000004098457,3.157743e-7,0.000006346012,0.00001709919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01489351,"threshold_uncertainty_score":0.4145338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1363391592449751,"score_gpt":0.4157473414208699,"score_spread":0.2794081821758948,"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."}}