{"id":"W4405303321","doi":"10.25683/volbi.2019.49.444","title":"ПЕРСПЕКТИВЫ РАЗВИТИЯ ТОРГОВЫХ ЦЕНТРОВ В РОССИЙСКОЙ ФЕДЕРАЦИИ","year":2019,"lang":"ru","type":"article","venue":"Бизнес, образование, право","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Distribution (mathematics); Christian ministry; Gross domestic product; Population; External trade; Product (mathematics); Russian federation; Business; Retail trade; Economics; Economy; Geography; International trade; Regional science; Economic growth; Commerce; Political 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":[0.002776172,0.000808898,0.0005596335,0.002442138,0.003468486,0.01144749,0.001139228,0.00256142,0.02965199],"category_scores_gemma":[0.007152616,0.0007016306,0.0009129373,0.001829423,0.009262512,0.006583001,0.003360631,0.00366229,0.01003171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004637928,"about_ca_system_score_gemma":0.007431171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007170198,"about_ca_topic_score_gemma":0.005663121,"domain_scores_codex":[0.9956916,0.001077628,0.0002448946,0.00084458,0.001702219,0.0004391718],"domain_scores_gemma":[0.9964325,0.0009521703,0.0004107868,0.000528157,0.001317221,0.0003591161],"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":[0.00003283024,0.00002556217,0.0009960007,0.0001804273,0.00002479561,0.0002304449,0.002351314,0.0005766164,0.001246033,0.9529674,0.007083483,0.03428506],"study_design_scores_gemma":[0.00002977816,0.00005576977,0.003296361,0.0003821111,0.00005038629,0.0006644749,0.004301424,0.001329189,0.002396283,0.510708,0.4767045,0.00008180335],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02407702,0.01151084,0.07877499,0.01784514,0.001552228,0.000164166,0.0005724019,0.0003506274,0.8651526],"genre_scores_gemma":[0.662772,0.01639382,0.08310604,0.003111324,0.001218922,0.0006265356,0.0006921209,0.0004939822,0.2315852],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02965199,"threshold_uncertainty_score":0.09919584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01759140962543337,"score_gpt":0.2755214973953609,"score_spread":0.2579300877699275,"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."}}