{"id":"W7133793565","doi":"10.5281/zenodo.18874780","title":"Strategic Approaches to Enhancing Digital Access in Rural South Africa","year":2008,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"ICT Impact and Policies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Government (linguistics); Focus group; Subsidy; Digital divide; Stakeholder; Internet access; Thematic analysis; Digital inclusion; The Internet","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":[0.001807669,0.0003802938,0.0001818209,0.001080867,0.003554914,0.002735935,0.0008279884,0.0009716807,0.006613319],"category_scores_gemma":[0.002893543,0.000238117,0.000204958,0.001894042,0.002733815,0.001492082,0.006050257,0.0008235529,0.0003640276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003548406,"about_ca_system_score_gemma":0.01141565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006519046,"about_ca_topic_score_gemma":0.01461003,"domain_scores_codex":[0.9984632,0.001001116,0.00002958347,0.00005488664,0.0000806,0.0003706488],"domain_scores_gemma":[0.9990112,0.0004687656,0.0001145742,0.0000419088,0.00007492865,0.0002886734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002714661,0.001206986,0.02688101,0.003501132,0.00007825433,0.007232551,0.2935538,0.007611947,0.01980155,0.3168807,0.009468396,0.3135122],"study_design_scores_gemma":[0.0001874648,0.0006919987,0.02603806,0.001342455,0.00008097745,0.00138135,0.5617808,0.006100512,0.005283199,0.1041682,0.2928836,0.00006148255],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8261827,0.001884136,0.01838613,0.01931135,0.00007156741,0.001500312,0.0001047731,0.00008924835,0.1324697],"genre_scores_gemma":[0.9859001,0.0009713988,0.007221257,0.0003890711,0.000005476195,0.0003339429,0.00001947579,0.000006425411,0.005152787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006613319,"threshold_uncertainty_score":0.02574569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1346408831248828,"score_gpt":0.240501112234408,"score_spread":0.1058602291095253,"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."}}