{"id":"W3108508050","doi":"10.1080/19186444.2020.1849936","title":"Influence of digital economy on youth unemployment in West Africa","year":2020,"lang":"en","type":"article","venue":"Transnational Corporation Review","topic":"Economic Growth and Development","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Unemployment; Youth unemployment; Unit root; Unemployment rate; The Internet; Economics; Estimation; Development economics; Economic growth; Econometrics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001171112,0.0001227355,0.0002043126,0.001279891,0.0005746591,0.001429782,0.0001675626,0.0004400298,0.002421734],"category_scores_gemma":[0.003245309,0.00008443122,0.0001932161,0.00213423,0.0004564353,0.0008544681,0.0006945811,0.0005814515,0.0001148042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001200563,"about_ca_system_score_gemma":0.003420257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02165923,"about_ca_topic_score_gemma":0.04756558,"domain_scores_codex":[0.999542,0.0001720553,0.00004263288,0.00002409118,0.00005949067,0.0001597783],"domain_scores_gemma":[0.9979985,0.0008831258,0.0005463834,0.00001933941,0.0003242961,0.0002282394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001194051,0.0002941981,0.2743308,0.02303499,0.0006297905,0.002813007,0.02550356,0.0009147411,0.001615873,0.03184259,0.02396909,0.6138574],"study_design_scores_gemma":[0.00004987451,0.0003395847,0.675792,0.01903983,0.000996222,0.0008190027,0.0531028,0.0003334077,0.0007757223,0.001741034,0.2469716,0.00003892957],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3908771,0.5732968,0.00009092406,0.01490073,0.0006863764,0.00002424263,0.000396987,0.000003994917,0.01972291],"genre_scores_gemma":[0.7323846,0.265159,0.00005472243,0.0008309428,0.0002273147,0.00001179847,0.00007674181,0.00000346093,0.001251468],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02165923,"threshold_uncertainty_score":0.04306632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05419701933853083,"score_gpt":0.2339623743759026,"score_spread":0.1797653550373717,"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."}}