{"id":"W2761513927","doi":"10.35648/20.500.12413/11781/ii164","title":"Geographies of Information Inequality in Sub-Saharan Africa","year":2014,"lang":"en","type":"report","venue":"","topic":"ICT Impact and Policies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; International Development Research Centre","keywords":"The Internet; Mobile phone; Geography; Inequality; Internet access; Phone; Telecommunications; Business; Computer science; World Wide Web; Mathematics","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":[0.0004481619,0.0001665621,0.0003647483,0.0006552736,0.00000893043,0.00001895876,0.0001044078,0.0002365122,0.00005188386],"category_scores_gemma":[0.00008947132,0.0001460635,0.00009186577,0.0002924733,0.00002661501,0.0001895928,0.00001972608,0.0001853542,0.00003059662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004955338,"about_ca_system_score_gemma":0.0000559933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001801109,"about_ca_topic_score_gemma":0.0003254931,"domain_scores_codex":[0.9989384,0.00001498621,0.0005354625,0.0000244055,0.0002921765,0.0001945804],"domain_scores_gemma":[0.99952,0.00004632872,0.00009654428,0.0002098875,0.00009350576,0.00003370382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000188399,0.00004481106,0.0184603,0.009656786,0.0002655684,9.0231e-7,0.00986299,0.004701968,0.0003435006,0.0005963836,0.9132639,0.04278403],"study_design_scores_gemma":[0.0001471457,0.00002627584,0.05207829,0.0001893698,0.00002126836,0.000003282847,0.00008905573,0.0002391129,0.001363601,0.000112607,0.9454202,0.0003097537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.168411,0.002387324,0.0007783836,0.00002092902,0.0008972005,0.0002615419,0.0001410925,0.0003041026,0.8267985],"genre_scores_gemma":[0.9905648,0.008765795,0.00003031992,0.0000125615,0.000107672,0.00001306044,0.0001880736,0.00001908536,0.0002986912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8264998,"threshold_uncertainty_score":0.5956295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02271995744999979,"score_gpt":0.2555063555358918,"score_spread":0.232786398085892,"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."}}