{"id":"W6912816980","doi":"10.5683/sp2/reoay6","title":"Revenue, Expenditure, Assets, and Liabilities (REAL) user files","year":2020,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Revenue; Government (linguistics); Public finance; Per capita; Population; Government revenue; National accounts; Fiscal year","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":[0.001140151,0.001102006,0.0009612032,0.004038101,0.0008409399,0.002260184,0.001845019,0.0008237707,0.07401002],"category_scores_gemma":[0.00719372,0.0006667293,0.0006575575,0.01043768,0.0003253632,0.001512433,0.001259505,0.001554575,0.09060015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003623169,"about_ca_system_score_gemma":0.006092137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1552395,"about_ca_topic_score_gemma":0.1860673,"domain_scores_codex":[0.9986558,0.000101486,0.0001617908,0.0002875238,0.0005272369,0.0002660926],"domain_scores_gemma":[0.9958275,0.0005799407,0.0004333966,0.0007429771,0.002077054,0.0003389973],"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":[0.00002293297,0.000009601079,0.0009043893,0.0001202395,0.00000645188,0.000008440195,0.00001814072,0.0001060701,0.0000395281,0.0006579811,0.9966522,0.001454004],"study_design_scores_gemma":[0.00004120888,0.000004874641,0.005700425,0.0001234208,0.000007169209,0.00002121998,0.00007777647,0.000173579,0.0002339177,0.0004990411,0.9930997,0.00001755257],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000577356,0.000008189422,0.00002353542,0.00002167448,0.000006115295,0.000007239571,0.9989995,0.00008535389,0.0007905634],"genre_scores_gemma":[0.000325153,0.00002458524,0.0001731198,0.00002221581,0.000004902215,0.00006078467,0.9981335,0.00005330881,0.001202446],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1552395,"threshold_uncertainty_score":0.3086717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115014019099784,"score_gpt":0.2717630352230229,"score_spread":0.250612895032025,"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."}}