{"id":"W3117988331","doi":"10.5539/ijef.v13n1p61","title":"Causes and Consequences of Idle Youth in Guatemala","year":2020,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Latin Americans; Unemployment; Economics; Demographic economics; Unemployment rate; Private sector; Estimation; Youth unemployment; Regression analysis; Economic growth; Political science; Sociology; Demography; Statistics","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":[0.0002278177,0.0001926113,0.0002039862,0.001428576,0.001578459,0.000662663,0.0004177385,0.0003842558,0.002175664],"category_scores_gemma":[0.001267068,0.0001713925,0.0003626539,0.001275065,0.0009321656,0.0003205506,0.001849012,0.0005496384,0.0001298172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0013719,"about_ca_system_score_gemma":0.001014318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07552692,"about_ca_topic_score_gemma":0.1152083,"domain_scores_codex":[0.999606,0.00007624911,0.00002590043,0.00003451456,0.0000533534,0.0002041108],"domain_scores_gemma":[0.9992925,0.00006025983,0.0003674672,0.00002934131,0.00007506183,0.0001753314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002302996,0.00001601959,0.9908301,0.00003151012,0.00002006532,0.001373719,0.002051067,0.0000697072,0.0001604896,0.0004579102,0.000635436,0.004330936],"study_design_scores_gemma":[9.537762e-7,0.00001108697,0.9944927,0.00003217621,0.00001028792,0.0005845798,0.003859228,0.00008345621,0.00004996732,0.0001154231,0.0007561769,0.000004061081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967475,0.000666628,0.00003060573,0.0007879109,0.00001277643,0.000007557539,0.0002948674,0.00001024558,0.001441958],"genre_scores_gemma":[0.9993798,0.0003320408,0.00001296946,0.00004390823,0.000005707077,0.000004350183,0.00009320111,0.00000167113,0.0001264479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07552692,"threshold_uncertainty_score":0.1501746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03091171559506826,"score_gpt":0.2734495778874461,"score_spread":0.2425378622923779,"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."}}