{"id":"W6888902219","doi":"10.24411/2500-1000-2020-10327","title":"СРАВНИТЕЛЬНЫЙ АНАЛИЗ НАЛОГОВЫХ СИСТЕМ РОССИИ, КАНАДЫ, ШВЕЙЦАРИИ И ЮЖНОЙ КОРЕИ","year":2020,"lang":"ru","type":"article","venue":"CyberLeninK (CyberLeninka)","topic":"Education, Law, and Society","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Tax reform; Economic analysis; Tax revenue; Tax credit","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":[0.002981699,0.0007759195,0.0005356097,0.002776602,0.005048534,0.01324648,0.001272954,0.002663807,0.01745808],"category_scores_gemma":[0.007571112,0.000618734,0.0008384411,0.002841545,0.01123475,0.007546056,0.004170492,0.003094325,0.004859093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005574319,"about_ca_system_score_gemma":0.0101832,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007866588,"about_ca_topic_score_gemma":0.009291844,"domain_scores_codex":[0.9944927,0.001622141,0.0002382617,0.0009349901,0.002167871,0.000544125],"domain_scores_gemma":[0.9950642,0.001858559,0.0006494142,0.0006315003,0.001283212,0.0005130332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003424196,0.00003995308,0.001930125,0.0001996877,0.00002015482,0.0003950598,0.005947887,0.0005015329,0.001363169,0.9454032,0.004533261,0.03963176],"study_design_scores_gemma":[0.00002870035,0.0000675379,0.006758887,0.0005067974,0.00006172345,0.00102829,0.01073725,0.001475871,0.002829406,0.5510507,0.4253713,0.00008350912],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04366953,0.01189034,0.07828522,0.01572884,0.000999817,0.0001882346,0.0003901898,0.0002331589,0.8486147],"genre_scores_gemma":[0.7818027,0.01405171,0.06291676,0.001861389,0.0006935426,0.0004745259,0.0003955189,0.0002904732,0.1375133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9921334,"threshold_uncertainty_score":0.05840307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04566042871022696,"score_gpt":0.3123282287673234,"score_spread":0.2666678000570964,"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."}}