{"id":"W2339008636","doi":"","title":"Разработка финансового блока в квартальной макроэкономической модели Российской Федерации","year":2005,"lang":"ru","type":"article","venue":"Научные труды: Институт народнохозяйственного прогнозирования РАН","topic":"Economic and Technological Developments in Russia","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Russian federation; Central bank; Economics; Reflection (computer programming); Quarter (Canadian coin); Financial system; Macroeconomics; Economy; Economic policy; Monetary policy; Geography; Computer science","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":[0.0009976042,0.0002581947,0.0002793425,0.001483453,0.001796129,0.005421801,0.0003913999,0.000883545,0.008674198],"category_scores_gemma":[0.002349118,0.0003111802,0.0003431941,0.001194716,0.006033411,0.002434368,0.001688801,0.001196314,0.001957649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002435967,"about_ca_system_score_gemma":0.003144036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003060221,"about_ca_topic_score_gemma":0.003035325,"domain_scores_codex":[0.9987134,0.0003417979,0.00006149022,0.000209217,0.0005105135,0.0001636465],"domain_scores_gemma":[0.9989443,0.0003588171,0.0001669762,0.0001359854,0.0002739456,0.0001200188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004488476,0.00002620703,0.002304406,0.0001976507,0.00002347073,0.0002796792,0.006039369,0.0007520583,0.003852796,0.938263,0.001788378,0.04642814],"study_design_scores_gemma":[0.00003074255,0.0001112259,0.01547567,0.0003167546,0.00007074013,0.000833352,0.008173533,0.001651599,0.00704363,0.6503062,0.315898,0.00008854771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1757947,0.01283666,0.06591071,0.008498307,0.0005146168,0.0001281746,0.0004240524,0.0001929193,0.7356998],"genre_scores_gemma":[0.947226,0.003594033,0.01591949,0.0001634811,0.0001587337,0.0001204876,0.00009168001,0.00005943471,0.03266649],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008674198,"threshold_uncertainty_score":0.0290181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02657168363429326,"score_gpt":0.2895743684679832,"score_spread":0.2630026848336899,"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."}}