{"id":"W6912519794","doi":"10.5281/zenodo.3970441","title":"Voice and accountability and information technology for Latin America","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Accountability; Latin Americans; Information technology; Empirical research; Information and Communications Technology; Empirical evidence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001445998,0.0001736383,0.0002142235,0.001829231,0.0007769887,0.002364396,0.0001425709,0.0003297551,0.003412181],"category_scores_gemma":[0.005014651,0.00005175897,0.0003409953,0.002642628,0.001495813,0.0009912726,0.001605325,0.0004397071,0.0001159381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001928524,"about_ca_system_score_gemma":0.001613641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02056581,"about_ca_topic_score_gemma":0.01565844,"domain_scores_codex":[0.9989166,0.0005338028,0.00005314634,0.0001004084,0.0001464726,0.0002495545],"domain_scores_gemma":[0.9971981,0.001625624,0.0006309199,0.00009686359,0.0002885149,0.0001600226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004061048,0.0002826625,0.7834082,0.0003195361,0.0001416889,0.0003934648,0.02601049,0.001238828,0.001993307,0.06108774,0.001462213,0.1232558],"study_design_scores_gemma":[0.00002257896,0.0001610548,0.9290638,0.0001975381,0.00007472601,0.0001605995,0.03844769,0.00175599,0.0004294947,0.009241407,0.02042103,0.00002404306],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9473531,0.001880076,0.0007824828,0.001814541,0.00003349943,0.00002113358,0.0001367442,0.00002837474,0.04795002],"genre_scores_gemma":[0.99852,0.0003334731,0.0002158457,0.00007838174,0.00001560538,0.00001462565,0.00004921047,0.000004435435,0.0007684496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02056581,"threshold_uncertainty_score":0.04089218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0192254215818426,"score_gpt":0.2589388299031868,"score_spread":0.2397134083213442,"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."}}