{"id":"W7130967733","doi":"10.5281/zenodo.18731868","title":"ICT Infrastructure Development and Economic Growth in Ethiopia,","year":2001,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Economic Growth and Development","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Information and Communications Technology; Investment (military); Panel data; Developing country; Regression analysis; Information technology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004607048,0.0001129978,0.000115098,0.0002463048,0.0006441234,0.0005807613,0.0008842858,0.00005286921,0.0008372242],"category_scores_gemma":[0.00007621512,0.0001227208,0.00001444162,0.0002196528,0.00005086198,0.0003992666,0.001206991,0.0001748952,0.002035961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002442498,"about_ca_system_score_gemma":0.00001469897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001539758,"about_ca_topic_score_gemma":0.00000191008,"domain_scores_codex":[0.9988668,0.00008525801,0.0002460377,0.000394223,0.0001060549,0.0003016128],"domain_scores_gemma":[0.9994732,0.00001579349,0.00005957844,0.0002294061,0.00007217962,0.0001498771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005506897,0.0001075081,0.00328532,0.00008215824,0.00005532512,0.00008930785,0.01319644,0.0002025718,0.0003267598,0.1661651,0.06050498,0.7559294],"study_design_scores_gemma":[0.0005764925,0.00004798987,0.05578709,0.00001644219,0.000001020061,0.0001775966,0.00009966471,0.001360853,0.0004362943,0.001914752,0.9393637,0.0002181511],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8053582,0.0001138517,0.03814336,0.00205281,0.0002825876,0.0004420101,0.00001134779,0.00073531,0.1528605],"genre_scores_gemma":[0.9902632,0.0001068941,0.008621023,0.0003284462,0.00004605328,5.84374e-8,0.00008186674,0.0002516092,0.0003008702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8788587,"threshold_uncertainty_score":0.9987411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01809674731740783,"score_gpt":0.2093417119525914,"score_spread":0.1912449646351836,"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."}}