{"id":"W3155544541","doi":"10.28995/2073-6304-2021-1-56-70","title":"TIMELY AND ADEQUATE MEASURES TO SUPPORT THE RUSSIAN ECONOMY AND POPULATION DURING THE PANDEMIC","year":2021,"lang":"en","type":"article","venue":"RSUH/RGGU Bulletin Series Economics Management Law","topic":"Economic, Social, and Public Health Issues in Russia and Globally","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Government (linguistics); Economic recovery; Business; Quarter (Canadian coin); Depreciation (economics); Economic sector; Economy; Russian economy; Pandemic; Christian ministry; Economic policy; Economic growth; Economics; Coronavirus disease 2019 (COVID-19); Political science; Geography; Economic system","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002881875,0.0002513846,0.0003968337,0.0000763608,0.00111021,0.001452418,0.0006208978,0.0000988723,0.001145821],"category_scores_gemma":[0.00008342592,0.0001768734,0.00009425379,0.000139401,0.0002556973,0.0003300759,0.0006620946,0.0001642926,0.000360711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001084245,"about_ca_system_score_gemma":0.00005193432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003427367,"about_ca_topic_score_gemma":0.001985824,"domain_scores_codex":[0.9974879,0.0002394132,0.0008780798,0.0007463413,0.0001681527,0.0004801156],"domain_scores_gemma":[0.9983142,0.0003502871,0.0002983565,0.0007620252,0.00004914024,0.0002260141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006317665,0.00001607496,0.01537064,0.00003101684,0.0001020869,0.000009047289,0.0009590998,0.0001781228,4.12561e-7,0.9606377,0.006010436,0.01662221],"study_design_scores_gemma":[0.0003269925,0.00004040495,0.06091423,0.000008781017,0.00002440526,0.00002798996,0.002418592,0.00003964597,0.000004982478,0.04895243,0.8870223,0.0002192752],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5390673,0.0006270065,0.00008325571,0.1112523,0.0009624935,0.0008597453,0.00004905988,0.00007341558,0.3470254],"genre_scores_gemma":[0.9645441,0.001284841,0.0004519314,0.009121602,0.0003080212,0.00009376252,0.00001727619,0.00002704192,0.02415139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9116852,"threshold_uncertainty_score":0.9997672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04583465938148916,"score_gpt":0.3090261988965218,"score_spread":0.2631915395150327,"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."}}