{"id":"W2994727651","doi":"10.31752/idea.2019.40","title":"The Global State of Democracy Indices Codebook, Version 3","year":2019,"lang":"en","type":"book","venue":"","topic":"Political Conflict and Governance","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"Aarhus Universitet","keywords":"Democracy; Codebook; Conceptualization; State (computer science); Political science; Index (typography); Computer science; Politics; Law; Algorithm; Artificial intelligence","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":[0.006022888,0.0006513706,0.001042546,0.006297608,0.001419369,0.006285347,0.00196578,0.0008487384,0.1301908],"category_scores_gemma":[0.04276745,0.0007025104,0.0006901438,0.016055,0.0007542781,0.004372011,0.003194025,0.002867087,0.08754388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004227846,"about_ca_system_score_gemma":0.01357776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02414674,"about_ca_topic_score_gemma":0.03495378,"domain_scores_codex":[0.9952493,0.001071777,0.001011378,0.0004416214,0.001953397,0.0002725338],"domain_scores_gemma":[0.9818816,0.005074824,0.0010007,0.001853278,0.009459534,0.0007300384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004602204,0.00002941618,0.001245826,0.0006691198,0.000008931791,0.00002167712,0.0004158544,0.0003920209,0.0001048848,0.01907972,0.9097666,0.06822006],"study_design_scores_gemma":[0.00002226548,0.00000984949,0.002785323,0.0005316783,0.000005664713,0.00003481327,0.0002856026,0.0002671402,0.0001177015,0.01143398,0.9844802,0.00002577778],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002235556,0.001199327,0.02189069,0.001731394,0.0008134443,0.003931301,0.8279831,0.002805609,0.1374096],"genre_scores_gemma":[0.009800463,0.002164007,0.05198247,0.001027651,0.0001728371,0.01502861,0.8490769,0.003775258,0.06697178],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1301908,"threshold_uncertainty_score":0.4355316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01537956883197719,"score_gpt":0.3036794168495187,"score_spread":0.2882998480175415,"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."}}