{"id":"W7133183885","doi":"10.5281/zenodo.18836713","title":"5G in Cape Verde: Replicating Studies on Digital Transformation Perspectives","year":2006,"lang":"en","type":"article","venue":"Open MIND","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":"Digital transformation; The Internet; Internet access; Government (linguistics); Investment (military); Digital divide","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":[0.004269742,0.0005224959,0.0004868657,0.003375879,0.001938541,0.001949253,0.001486508,0.0004783907,0.005135],"category_scores_gemma":[0.01815391,0.0002760018,0.0004078096,0.005048785,0.002094392,0.001639614,0.002007853,0.0007147708,0.0001588711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00897588,"about_ca_system_score_gemma":0.003507566,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5538617,"about_ca_topic_score_gemma":0.5671453,"domain_scores_codex":[0.9967955,0.001568464,0.0001533783,0.0005148137,0.0005167222,0.0004510147],"domain_scores_gemma":[0.990472,0.005066974,0.001505336,0.00124463,0.001504393,0.0002068068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008762287,0.0003844291,0.6462266,0.003844673,0.0007893474,0.007476999,0.09398327,0.007106614,0.002828806,0.06421595,0.007415742,0.1648514],"study_design_scores_gemma":[0.00005324791,0.0001786693,0.8750971,0.001458916,0.0002613952,0.0004223482,0.07010929,0.002621016,0.001408131,0.00201646,0.04631962,0.00005384985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9543867,0.004758992,0.001331309,0.002503164,0.00006652812,0.0002146127,0.001335194,0.00001309359,0.03539054],"genre_scores_gemma":[0.9974505,0.0008468771,0.0004037806,0.0001057755,0.000008376419,0.00003447543,0.0001779403,0.000003374369,0.0009689099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5538617,"threshold_uncertainty_score":0.8975314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02930747411912268,"score_gpt":0.3084021228392951,"score_spread":0.2790946487201724,"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."}}